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M. Fourteau1, K. Virecoulon Giudici1, Y. Rolland1,2, B. Vellas1,2, P. de Souto Barreto1,2


1. Gerontopole of Toulouse, Institute of Ageing, Toulouse University Hospital (CHU Toulouse), Toulouse, France; 2. UPS/Inserm UMR1027, University of Toulouse III, Toulouse, France.

Corresponding Author: Marie Fourteau, Gérontopôle de Toulouse, Institut du Vieillissement, 37 Allées Jules Guesde, F-31000 Toulouse, France, Phone: (+33) 561 145 664, Fax: (+33) 561 145 640, e-mail: mariefourteau@hotmail.com

J Aging Res & Lifestyle 2020;9:16-25
Published online September 3, 2020, http://dx.doi.org/10.14283/jarlife.2020.6



Background: Recently, the World Health Organization defined five domains of intrinsic capacity (IC), composed of physical and mental capacities linked to body functions, and that contribute to healthy aging: locomotion, cognition, psychological, vitality and sensorial. In the past decade, studies investigating the effects of concomitant lifestyle interventions (also called multidomain interventions) on one or several IC domains have been developed. The aim of this study is to synthetize the scientific literature about the associations between multidomain lifestyle interventions and IC domains. Methods: We conducted a narrative review of randomized controlled trials examining the effects of multidomain lifestyle interventions on at least one IC domain among older people. Multidomain intervention was defined as the presence of at least two of the following lifestyle interventions: physical activity/exercise, nutrition, cognitive stimulation, and management of cardiovascular risk factors (eg, smoking, alcohol consumption). Results: Multidomain interventions were associated with improvements on locomotion (as measured by performance-based tests of lower-limb function) and vitality (as measured by handgrip strength); benefits on cognitive function were also found, in particular among populations at increased risk of dementia and when operationalizing strong multidomain interventions (eg, using regular exercise training instead of physical activity advices). No study investigated the effects of multidomain lifestyle interventions on the sensorial domain (hearing and/or vision). The modalities composing the multidomain interventions and intervention length, as well as study population, substantially varied across studies; the most common combination of interventions was physical activity- and nutritional-related interventions. Conclusion: Available evidence is still limited, but literature suggests a positive effect of multidomain lifestyle interventions on IC domains, in particular locomotion. Further studies are still needed on this topic, in particular, studies exploring the effects of multidomain lifestyle interventions on the sensorial domain, as well as on a composite measurement of all IC domains.

Key words: Intrinsic capacity, aging, multidomain intervention, locomotion, cognition, psychological, vitality, vision, hearing.

Abbreviations: ADL: Activity of Daily Living; CAIDE: Cardiovascular Risk Factors, Aging, and Incidence of Dementia; FINGER: Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability; FIT: Frailty Intervention Trial; IADL: Instrumental Activities of Daily Living; IC: Intrinsic Capacity; MAPT: Multidomain Alzheimer Preventive Trial; MDI: Multidomain Intervention pre; DIVA: Preventive of Dementia by Intensive Vascular care; RCT: Randomized Controlled Trial; SPPB: Short Physical Performance Battery; WHO: World Health Organization.



Functional decline often occurs during aging. Recently, the World Health Organization (WHO) (1) supported the idea that healthy aging should not be defined as the absence of diseases, but as a process to develop and maintain functional abilities during aging. In this context, experts from WHO, in collaboration with academic researchers around the world, developed the theoretical framework of intrinsic capacity (IC) (2), ie, the combination of all physical and mental capacities of an individual. These experts proposed to divide IC through five domains that strongly contribute to healthy aging (1, 2): psychological, cognitive, locomotion, vitality and sensory. Therefore, developing strategies that benefit multiple domains of IC would probably lead to the promotion of healthy aging.
Several lifestyle interventions have been found to benefit specific domains of IC. Physical exercise improves locomotion (3) and may improve cognitive function (4, 5) as well as psychological outcomes, whereas cognitive training improves cognitive function6; nutritional aspects are also associated with different IC domains (7, 8). From the observation that different lifestyle interventions may lead to improvements in different clinical outcomes, the benefits of the combination of different lifestyle interventions, the so-called “multidomain intervention”, have been recently explored. Multidomain lifestyle interventions would potentially have synergistic and positive effects on IC domains. However, as far as we know, no study gathered the available scientific evidence of the effects of multidomain lifestyle interventions on the five domains of IC. Moreover, the best combination of lifestyle interventions to improve older adults’ function remains to be elucidated.
This narrative review aimed to synthetize the scientific findings regarding the effects of randomized controlled trials (RCT) of multidomain lifestyle interventions on the domains of IC among older adults.



Eligibility criteria

Articles were eligible for this review if they were written in English or French; reported the results of a RCT regarding the effects of multidomain lifestyle interventions on one or several IC domains; included older adults (participants’ minimum age or the mean age of the study population ≥ 60 years). Multidomain lifestyle intervention was defined as the concomitant presence of at least two of the following lifestyle interventions: physical activity/exercise, nutrition, cognitive stimulation, and management of cardiovascular risk factors (eg, smoking, alcohol consumption).
The domains of IC were defined as follows:
1. Locomotion. Measured using the Short Physical Performance Battery9 (SPPB) or gait speed.
2. Cognition. Measured using a validated neuropsychological test or a battery of tests for older adults.
3. Psychological. Measured using a validated scale of depressive symptoms for the elderly (such as the Geriatric Depression Scale – GDS).
4. Vitality. A consensual way of measuring the concept of vitality is not yet established10. We opted to operationalize this domain by using the handgrip strength10, which is a vital sign during aging11 and is associated to nutritional status12.
5. Sensory. Measured using validated tests for vision (eg, near/distance visual acuity) and hearing (eg, audiometry, Whisper test) capacities in older people.

The exclusion criteria comprised studies using a single lifestyle intervention or comparing different types of lifestyle interventions without assessing the effects of the combination of at least two interventions; mean age of the study population< 60 years; and samples of participants specifically presenting MCI or dementia.

Search strategy

Potentially eligible studies were searched on PubMed database from November 2019 to July 2020, and in the reference lists of previous literature reviews and other publications (13, 14), as well as authors’ personal files. For the search, key-words related to the population (eg, elderly), the intervention (eg, multidomain), and the study design (eg, random) were used. All the search terms are summarized in Supplementary Table 1.

Table 1
Characteristic of the included studies

a. Singapore; b. Japan; c. Taïwan; d. Sweden; e. Austria; f. Australia; g. Finland; h. France; i. Holland; j. Korea;


Data extraction

One author extracted the information of selected publications on: study population characteristics, intervention, IC domains investigated, and findings of the effects of multidomain lifestyle intervention on the IC domain. This review included 23 articles. Characteristics of key articles/studies and interventions are, respectively, presented in Table 1 and Table 2 (15–38).

Table 2
Summary of Interventions and Results of the included studies

k. Instrumental Activity of Daily Living; l. Activity of Daily Living; m. Mini Mental State Examination; n. Primary Care Evaluation of Mental Disorders; o. Body Mass Index; p. Fat Free Mass; q. Bone Mineral Density; r. x2 factorial design; s. The modified organic Brain Syndrome Scale; t. Geriatric depression Scale 15 items; u. Swedish version of the clinical outcome variables; v. MA-I : Mental activity Intervention; w. MA-C: Mental Activity Control; x. EX-I : Exercise intervention; y. EX-C : Exercise Control; z. Physiological Profile Assessment; aa. Basic activities of daily living; bb. Further stratified into free recall; cc. Digital Substitution Symbol Test; dd. Trail Making test; ee. Categorical Naming Test; ff. Controlled Oral World Association Test;; gg. Trunk Fat Mass; hh. Diagnotic and Statistical manuel of Mental Disorders IV; ii. Visual Association test



The articles/studies were performed in Japan (18, 20), Australia (15, 16), Korea (37), Singapore (17), Taiwan (19), Austria (22), Finland (21, 27, 28, 35), France (24–26, 32, 33, 38), the Netherlands (29, 30), the United States (36) and Sweden (21, 23). The sample size varied from 80 to 1680 participants across studies, with a mean age higher than 65 years old for all studies. Intervention length varied from 2 months to 6 years. The most used multidomain lifestyle intervention was a combination of physical activity, nutritional and cognitive interventions (17, 24–28, 35, 38); a combination of physical activity and nutritional intervention (18–21) or individually-tailored multifactorial interventions (including exercise, nutritional and psychological interventions depending on individual’s needs) (15, 16, 34). A combination of physical activity and cognitive intervention (36) or physical activity, nutritional intervention and health education (22, 23); as well as assessments of cardiovascular risk factor and adapted advice were also observed (29, 30). Thus, the advices and encouragement in physical, cognitive and social activities, in combination with rewards for good health behaviours (37) were included.
About the IC domains investigated, locomotion (15–18, 20, 21, 24, 27, 34, 35) and cognition (23–30, 36, 37) capacities were the most frequent IC domains investigated, followed by the vitality domain (as measured by handgrip strength) (16, 18–20, 22, 32), and then the psychological domain (15, 16, 19, 23, 27, 33). One study has investigated the effects of a multidomain lifestyle intervention on a composite score of IC (38.) This analysis, using data of the MAPT study, has included the following four IC domains: locomotion, cognition, psychological and vitality.
No study has assessed the effects of multidomain lifestyle interventions on a valid measurement of vision or hearing capacities (sensorial domain).
Effects of multidomain lifestyle intervention on IC domains in elderly persons

IC Z-score

Recently, one study from MAPT38 has investigated the effects of a multidomain lifestyle intervention (composed by physical activity advices, nutritional counselling, and cognitive training), with or without omega-3 supplementation, on an IC Z-score including four domains (ie. locomotion, psychology, cognition and vitality). After three years, the IC Z-score decreased among all groups, but no significant difference was found between groups.
This article was the first to study the effects of a multidomain lifestyle intervention on a composite score of intrinsic capacity. Further studies are needed in order to be able to conclude on this topic.


Some publications (15–18, 20, 21, 24, 27, 34, 35) evaluated the effects of multidomain lifestyle interventions on locomotion. Regarding gait speed, results of at least three articles (15, 18, 34) showed an improvement of gait speed in the multidomain intervention group. This significant increase was observed in particular among participants with slow gait speed and participants with higher levels of frailty. Besides, the combined physical, nutritional and psychological intervention (15) showed also an improvement of gait speed in frailty older adults. However, other studies (17, 20, 21, 24) did not find any effects of multidomain intervention on walking speed.
At least five articles (15, 16, 24, 34, 35) used the SPPB score in order to measure the mobility of participants. The multidomain approach composed of individually-tailored interventions (including exercise, nutritional, and psychosocial support depending on individual’s needs) described in three publications (15, 16, 34) had positive effects on the SPPB score after 12 months, but not at 3 months of follow-up. Additionally, the combination of physical activity, nutritional counselling, cognitive training, social activities and management of metabolic and vascular risk in the Finnish Geriatric Intervention Study to Prevent Cognitive Impairment and Disability (FINGER) (35) showed a protective effect of physical decline for chair rise test, but no effects were observed for SPPB score (27). However, another study with an intervention composed by physical activity, nutritional counselling and cognitive training, with or without omega-3 polyunsaturated fatty acid supplementation, had no effects on the SPPB score (24).
Overall, despite still limited findings, part of the currently scientific evidence about SPPB supports a positive effect of multidomain lifestyle intervention. In contrast, concerning gait speed, most of the included studies found no effects of multidomain lifestyle intervention.


Several articles (23–30, 36, 37) assessed cognitive capacity after a multidomain intervention. The assessment of cognitive function varied across studies. Executive function was an outcome in two studies (26, 27), and was improved in one of them (27). In the FINGER Study (27), both intervention and control groups (usual health advice) had an increase on cognitive function (executive function and processing speed), but this improvement was significantly higher in the intervention group after 24 months. Despite using magnetic resonance imaging (MRI) (28), authors were unable to explain the effects of this multidomain intervention on global cognitive function by some structural brain mechanisms. One study (37)proposing bimonthly counseling-visits with rewards for good behavior showed superior cognitive function (ie. improvement of MMSE score) compared to the control group (ie. standards and usual care), identifying participation at cognitive activities as a protector factor against cognitive decline. The Mental Activity and eXercise (MAX) Trial (36) enrolled inactive older adults with cognitive complaints in home-based mental activity and class-based physical activity for 12 weeks, and found an improvement of global cognitive scores over time but with no differences between intervention and active control groups, what may suggest that, for this population, the amount of activity would be more important than its type.
Moreover, analysis of the effects of interventions in the Multidomain Alzheimer Preventive Trial (MAPT study) (25) restricted to the subgroup of older adults with higher risk of dementia due to cardiovascular risk factors (CAIDE dementia risk score) showed an improvement of the cognitive function in multidomain groups; similar results were found in the subgroup with high β-amyloid load in the brain (24). However, it is important to highlight that in the full sample of the MAPT study (24) as well as in the Preventive of Dementia by Intensive Vascular care (preDIVA) (29, 30) no effects were observed on cognitive function, including among those with an increased dementia risk score. Besides, the addition of rewards for good behaviours at the combined nutritional and cognitive activities (23) did not show beneficial effect on cognitive function.
Therefore, the effects of multidomain lifestyle intervention on cognitive function are not a consensus. On the one hand, two studies presented positive effects for this type of intervention. These results corroborate with those of another study comparing the effects of physical activity, cognitive training and the combination of both with a control group (39). On the other hand, two cohorts did not find any results on cognitive function (24, 25, 29, 30). Thus, the effectiveness of multidomain lifestyle interventions on cognitive function still demands further exploring.


Only few studies (15, 16, 19, 23, 27, 33) tested the effects of multidomain interventions on psychological function among elderly subjects. The results of these studies (15, 16, 19, 23, 27, 33) revealed no effects of multidomain interventions on depressive symptoms (measured by the GDS or the Center for Epidemiologic Studies Depression Scale – CES-D) in elderly people with frailty, memory complains or at risk of cognitive decline, after follow-ups varying from 3 months to 3 years.
So far, the available scientific evidence did not support any effects of multidomain intervention on the psychological domain of IC among older adults.


Some studies of multidomain RCT (16, 18–20, 22, 32) evaluated the effects of the intervention on handgrip strength. At least three studies showed significant positive effects of interventions – including individually-tailored interventions (physical activity, nutritional intervention, psycho-social support according to participants’ needs) (16); exercise and cognitive intervention (19); and exercise associated with nutritional intervention (22) – on handgrip strength. Effects were significant in follow-ups of 12 months or over.
We found two studies that showed no improvement from the multidomain intervention (including exercise training and nutritional supplementation of milk fat globule membrane (18); or physical activity, nutritional counselling, and cognitive training (32)) on handgrip strength. However, one study (20) comprising nutritional and physical intervention showed a decline in handgrip during post-intervention follow-up, after maintenance during the combined intervention.
In summary, effects of multidomain lifestyle intervention on handgrip strength in older adults are still mixed. Twos studies found positive effects, other two studies found no effects on vitality domain and one study did not find significant benefits on handgrip during intervention but showed a significant decline post-intervention. Thus, it is not possible to conclude on the effectiveness of multidomain lifestyle interventions on handgrip measure.

Final considerations

This is the first review focused on current evidence of the effects of multidomain lifestyle interventions on IC among elderly people. One of the findings revealed herein is the complete absence of studies considering the sensory domain (hearing and vision) as an outcome. Although positive effects of multidomain interventions on locomotion, cognition and vitality (handgrip strength) were observed, findings were globally mixed. Another important finding of this review is that, as far as we know, only one study investigated the effects of the multidomain intervention on a global IC score, operationalized by considering four of the five domains of IC, except the sensory domain (38). The limited evidence about this topic does not allow us to conclude whether or not multidomain interventions would globally affect intrinsic capacity. Further studies operationalizing IC are therefore necessary.
The absence of multidomain RCT examining intervention effects on the sensorial IC domain is understandable given the nature of this domain: improving vision and hearing would not be expected with nutritional counselling or stimulating physical activity, for example. However, it is possible that multidomain interventions could contribute to preventing sensorial impairments, in particular for vision, through the prevention and control of cardiovascular and metabolic conditions, such as hypertension and diabetes. The well-known associations of physical activity/exercise and the prevention/management of cardiovascular and metabolic diseases are well-established (40–42). In addition, studies including antioxidant supplementations (43, 44), or multidomain lifestyle intervention (including Mediterranean diet, physical activity, avoided smoking and sedentary behaviours) (45) suggested positive effects on the progress and prevalence of aging related macular degeneration. It can also be noted that in MAPT Study, preventive consultations (which were part of the multidomain intervention) included evaluation of vision and hearing deficits, with recommendations for management where necessary (46).
Although still limited, available evidence supports an effect of multidomain interventions on locomotion when exercise training is present. SPPB was improved in multidomain RCTs that operationalized exercise sessions (not only advices on physical activity), even though other trials with exercise sessions found no effects on locomotion outcomes. It is possible that multidomain interventions have an effect on global locomotion (SPPB) only when a comprehensive exercise training, with strength but also balance exercises, is comprised in the intervention; indeed, a multidomain trial (34), including exercise training with strength and balance exercises, had positive effects on SPPB, in particular among frail participants and those who were more compliant with the intervention.
Multidomain lifestyle interventions improved cognition among older adults when operationalizing strong interventions (27) or for subpopulation of individuals at increased risk of cognitive decline (25, 47). Indeed, the FINGER trial (27) had supervised strength and aerobic training, compared to other RCTs that restricted the physical part of the intervention to counselling (24). Moreover, FINGER (27) and MAPT (24), this latter showing positive effects of the multidomain intervention on cognition among people at high risk for dementia (ie, high both CAIDE dementia score and amyloid load in the brain), had strong cognitive training and were among the largest (well-powered) and longest multidomain RCTs. Therefore, it is possible that lifestyle multidomain interventions should have strong components for both cognitive and exercise training to increase cognitive function. Multidomain interventions may still benefit cognition with a less strong physical component in subpopulations at increased risk for clinically meaningful cognitive decline.
For the psychological IC domain, we did not find improvements of multidomain interventions on depressive symptoms (15, 19, 23, 33). It is possible that in order to improve the psychological domain of IC, an intervention with more important psychological content (eg, group-based activities focusing on social support) would be needed. It is also plausible to think, as it seems to occur for the cognitive IC domain, that multidomain lifestyle interventions would be more effective in a subpopulation at increased risk for depression.
The handgrip strength, composing the vitality domain, was improved in three studies (16, 19, 22), but not in two others trials (18, 32); therefore, literature on this topic is mixed. One major point regards the non-consensual definition of vitality: although we opted to operationalise this IC domain using handgrip strength, as in previous publications (10), another operational definition using nutritional status is attracting further attention, including the World Health Organization (48). Although handgrip is associated with nutritional status (12), they are distinct measurements. It is thus possible that nutritional status would respond differently to a multidomain lifestyle intervention; this is still truer since a nutrition-related component is found in nearly all multidomain interventions operationalized to date.
Taken together, findings suggest that, in the long term, multidomain interventions can bring beneficial effects to health. The magnitude of these benefits will vary according to the modalities of intervention composing the multidomain approach. Globally, long-term (one year or over) and strong (eg, composed by exercise training instead of physical activity counselling) interventions lead to benefits on specific IC domains. It should be noted, however, that this review found an important variability across studies regarding the modalities of intervention composing the multidomain intervention. This variability makes it difficult to compare their findings and to generalize their results. Moreover, the small quantity of studies with multidomain interventions in elderly people do not allow us to precisely define the more effective protocol to each IC domain. Such methodological differences may probably have contributed to the mixed findings gathered in the present work.



IC tend to decline during aging, reducing individuals’ resilience and increasing their vulnerability to adverse health outcomes. Multidomain interventions are an interesting approach to optimize the effects of combined lifestyle interventions on the different IC domains. This review gathered heterogeneous findings on the effects of multidomain interventions on the different IC domains. Although still limited, the evidence suggest multidomain interventions may benefit locomotion and, to a lesser extent, cognition and vitality (handgrip strength). Developing strategies for preserving IC is crucial and of high clinical interest in the scenery of integrated care for older adults. Therefore, further investigating the links of multidomain interventions with each IC domain, but also with a global measurement of IC (combining all domains) would importantly contribute to the topic.


Acknowledgments: The present work was performed in the context of the Inspire Program, a research platform supported by grants from the Region Occitanie/Pyrénées-Méditerranée (Reference number: 1901175) and the European Regional Development Fund (ERDF) (Project number: MP0022856).

Conflict of interest: The author(s) declare(s) that there is no conflict of interest regarding the publication of this article.

Ethical standard: All procedures followed were in accordance with the ethical standards.





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35. Kulmala J, Ngandu T, Havulinna S, et al. The Effect of Multidomain Lifestyle Intervention on Daily Functioning in Older People: LIFESTYLE INTERVENTION AND DAILY FUNCTIONING. J Am Geriatr Soc. 2019;67(6):1138-1144. doi:10.1111/jgs.15837
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L. Håglin1, L. Bäckman1, J. Linder2, L. Forsgren2, M. Domellöf2,3


1. Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, SE-901 87 Umeå, Sweden; 2. Department of Pharmacology and Clinical Neuroscience, Umeå University, SE-901 87 Umeå, Sweden; 3. Department of Psychology, Umeå University, SE-90187 Umeå Sweden

Corresponding Author: L Håglin, Department of Public Health and Clinical Medicine, Family Medicine, Umeå University, SE-901 87 Umeå, Sweden, lena.haglin@umu.se

J Aging Res Clin Practice 2018;7:156-162
Published online November 19, 2018, http://dx.doi.org/10.14283/jarcp.2018.26



Background: Cognitive decline and dementia are common non-motor problems in Parkinson’s disease (PD). The underlying aetiology is multifaceted and both chronic and reversible causes for cognitive decline are likely to be present. Malnutrition is frequent in the Parkinson population, both early and late in the disease, and nutritional deficiencies could play a role in some cognitive deficits. Objectives: The objective is to study the association between nutritional status with focus on iron intake and homeostasis, mild cognitive impairment (MCI), and PD dementia (PDD). Setting and Participants: This study included 73 out of 145 patients with PD participating in a population-based study in northern Sweden. Measurements: Registration of nutritional status by laboratory analyses of blood plasma and neuropsychological assessments at time of diagnosis were performed. MCI and PDD were assessed yearly up to ten years after diagnosis. Mini Nutritional Assessments (Full-MNA score) and plasma variables detecting iron homeostasis were compared between patients with MCI and patients with normal cognition (NC). Motor severity was measured using the Unified Parkinson´s disease rating scale III, (UPDRS III) and Hoehn and Yahr (H&Y) staging scale. Cox proportional Hazard model were performed to see if any variables that differed between MCI and NC could predict PDD at follow-up. Results: Patients with MCI at time of diagnosis had lower levels of plasma iron (P-Fe) and albumin (P-Albumin) as well as a lower score on Full-MNA score. Dietary intake of iron was higher in patients with MCI than in patients with NC (p = 0.012). In logistic regression models adjusted for age, sex, and UPDRS III, lower levels of P-Fe (p = 0.025) and P-Albumin (p = 0.011) and higher dietary iron intake (p = 0.019) were associated with MCI at baseline. A Cox regression model with dementia as endpoint revealed that lower levels of P-Fe increase the risk of dementia at follow-up with adjustments for age, sex, UPDRS III, and MCI at baseline (HR 95% CI = 0.87 (0.78-0.98), p = 0.021). Conclusions: Low P-Fe was associated with cognitive disturbance at baseline and predicted dementia up to ten years after diagnosis in patients with PD. Low P-Albumin and malnutrition assessed with Full-MNA score were associated with MCI at baseline but did not predict dementia at follow-up.

Key words: Cognition, dementia, iron deficiency, Parkinson’s disease.




Parkinson’s disease is a complex multifaceted disease with great variations in prognosis. Predicting the path the illness will take is next to impossible. Therefore, it is important to find predictors for different disease outcomes.
Cognitive decline and dementia are common non-motor problems in PD and the incidence of dementia is two to six times higher than in the general population (1).
At diagnosis, 20-40% of the populations have Mild Cognitive Impairment (MCI) (2 – 5). MCI at diagnosis increases the risk of Parkinson’s disease dementia (PDD), but not all patients with MCI develop dementia (5). Different patterns of cognitive decline have been connected to PDD. For example, impairment of semantic fluency and pentagon copying has repeatedly been shown to predict PDD (5,6). Low education level, postural instability, UPDRS (7), impaired olfactory function (8,9), and male sex has been connected to higher rates of PDD (10).
Cognitive impairment has been reported among elderly with malnutrition and iron deficiency (11, 12). Solfrizzi et al. (2006) presented a review on the nutrient-dementia risk pattern and suggested that more studies were needed to support the role of metals in progression of cognitive decline (13). A high iron intake has frequently been reported to increase the risk of PD, but no convincing evidence exists for an association between PDD and intake of iron. Cheng et al. (2011) reported that PD risk increased by 18% (RR 1.18, 95 % CI 1.02-1.37) by every 10-mg/day increment in iron intake (14). Powers et al. (2003) reported that a high intake of iron, especially in combination with high manganese intake, may be related to an increased risk of PD (15). In addition, Powers et al. (2009) reported that high iron intake together with a low intake of cholesterol may be associated with an increased risk of PD (16). On the contrary, a higher intake of iron, magnesium, and zinc was independently associated with a reduced risk of PD (17). Follow-up of two large cohort studies, including accumulated information on nutrient intake, revealed a higher risk of PD with a high intake of non-heme iron in combination with low vitamin C intake, while not with intake of heme iron (18).
This study investigated the association between nutritional status with a focus on iron intake and homeostasis in PD patients at time of diagnosis and risk of MCI and PDD at follow-up.




This community-based prospective study focuses on idiopathic forms of Parkinsonism in a catchment area (parts of Västerbotten county in northern Sweden) with 142 000 inhabitants (19). All suspected cases with idiopathic Parkinsonism were referred to the neurological department that employed all the neurologists involved in this investigation. From January 2004 through April 2009, 185 cases with Parkinsonism were identified. In total 145 patients fulfilled diagnostic criteria for PD at the next follow-up (up to 10 years). Of these, 73 were included in the study (Table 1). Because the remaining 72 non-participating patients came to follow-up without fulfilling the three-day dietary registration, they were not included for a blood sample. Individuals not participating in the three-day dietary registration were older (mean 73.5 years vs mean 69.1 years, p=0.006) and scored higher on the UPDRS III (29.2 vs 24.7 p=0.016) compared to those participating. There were no significant differences between the groups with regard to proportions of men and woman, total MMSE and MNA score.
A few patients refused to participate and were classified as drop outs. All participants were extensively examined during repeated visits the first month following initial contact. Information about demographics and disease history was obtained. All cases with suspected idiopathic Parkinsonism underwent a standardized clinical examination by a neurologist specializing in movement disorders.
To confirm the presence of PD, another specialist in movement disorders (blinded to the assessment of the previous examiner) evaluated a videotape of the patient undergoing the UPDRS III examination investigating PD related motor functions speech, facial expression, rigidity, tremor, posture, gait and bradykinesia (20). Patients were included if both examiners judged that they had fulfilled the clinical criteria for PD according to the UK Parkinson ’s Disease Society Brain Bank (UK PDSBB) criteria. Motor severity was measured using the Unified Parkinson´s disease rating scale III, (UPDRS III) and Hoehn and Yahr (H&Y) staging scale.

Table 1 Baseline variables (mean±sd) for the total PD group and for patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). P-values as a result from comparing variables between MCI and NC

Table 1
Baseline variables (mean±sd) for the total PD group and for patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). P-values as a result from comparing variables between MCI and NC

Abbreviations: UPDRS = Unified Parkinson’s Disease Rating Scale; H&Y = Hoehn & Yahr stage, median; ADL = Activity of daily living; PIGD = Postural instability Gait Disorder; Ind = Indeterminate; TD = Tremor dominance:


The UPDRS scoring was performed with patients on their regular medication when started on dopaminergic treatment. The motor subtype was classified as tremor dominant (TD), postural instability and gait difficulty (PIGD) or indeterminate (Ind) according to Jancovic et al (21). The MMSE was used as a screening instrument for global cognition.
The study was approved by the Regional Medical Ethics Board in Umeå, Sweden. Written informed consent was obtained from all participants.

Medication for PD

The levodopa equivalent daily dose (LEDD) was calculated at baseline and at follow-ups by use of a conversion factor for each of the anti-Parkinson medications (22). Information about LEDD at baseline revealed that only two patients had started anti-Parkinson treatment at time of diagnosis. At first follow-up (six months), all but nine patients had started treatment and about 50% of the patients had a LEDD <200 and 8% had >300. Medication was introduced over the first weeks after diagnosis. The nutritional investigation, including the blood sampling, was performed in a non-standardized manner according to drug therapy during this time. Thirteen patients started anti-Parkinson medication before the blood sampling.

Nutritional assessments

The Full Mini-Nutritional Assessment (MNA score), an international validated screening tool, was used to assess nutritional status and performed by the dietician concomitantly with anthropometrical measurements. The screening consists of 18 questions regarding anthropometry, diet, and health (23). MNA total scores between 24 and 30 points indicate optimal nutritional status and scores between 17 and 23.5 points indicate at risk for malnutrition.
Dietary data were collected from a three-day dietary registration (3-day DR) performed by the patients three days before a scheduled visit to the Department of Neurology. The subjects recorded in a protocol what they ate and drank during those three days. To describe portion sizes, they had access to a booklet with photographs and drawings of various foods and dishes. Standard household measures or package sizes were used for food items not included. Energy and nutrient intake were calculated using the dietary software program Dietist XP (Kost och näringsdata, Stockholm, Sweden), which employs the National Food Administrations food database (NFA database 2.00, Uppsala, Sweden).

Biochemical analysis

Blood samples at baseline were collected at admittance between 8 am and 4 pm in a non-fasting condition on the day when the patients were admitted for assessments of nutritional status. Plasma samples were collected and stored at -70◦C until iron, ferritin, albumin, and transferrin were measured. Transferrin saturation was calculated S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1) (Trf %). Analysis was performed in clinical routine in the accredited laboratory at Umeå University Hospital. Plasma levels of albumin and transferrin were analysed by Vitros PHOS Slides, Vitros ALB Slides, and Vitros TRFRN reagent on an Ortho Vitros 5.1 FS analyser.


A battery of neuropsychological tests was performed and used for MCI and PDD classification at baseline, one year, three years, five, eight, and ten years. For MCI classification, the MDS Task force guidelines were used (24). Since the battery of tests included a minimum of two tests in all domains except language, modified level II criteria were applied (25). For patients not performing the full neuropsychological testing, MCI classification was based on self-perceived cognitive decline and MMSE (cut-off ≤29) (26).  All but four patients with blood samples performed the neuropsychological evaluation at baseline. PDD was diagnosed according to published criteria by neurologists experienced in neurodegenerative disorders (27). In periods between the neuropsychological testing, PDD was diagnosed by decline in MMSE, decline in basic activities of daily living (ADL) (28) due to decreased cognition, and cognitive decline reported from patients and/or family member. In addition to MCI and PDD, composite scores for different cognitive domains (executive function, attention, language, visuospatial function, and episodic memory) were calculated based on means of the z scores for each individual test. Neuropsychological measures used for classification of Mild Cognitive Impairment and calculation of composite scores. Pentagon copying was not included in the calculation of composite scores.
Episodic memory: Free and Cued Selective Reminding Test (FCSRT) free recall, Brief Visuospatial Memory Test (BVMT) total, Brief Visuospatial Memory Test (BVMT) delayed.
Visuospatial function: Benton Judgement of Line Orientation (BJOLOT), pentagon copying from MMSE. Language function: Boston Naming Test. Working memory and attention: Digit span backwards, Trail Making Test part B. Executive function: Wisconsin Card Sorting Test (WCST) total errors, Wisconsin Card Sorting Test (WCST) preservative errors, Semantic fluency (animals in 60 seconds).

Data analyses

The results are presented as mean and standard deviation with min-max for each variable presented. Independent two-tailed tests were used to compare patients with MCI and NC. For non-normal distributed data and variables with skewed distribution, non-parametric tests were performed: the Mann-Whitney and the Wilcoxon Signed Ranks Test. Most variables were approximately normally distributed except for H&Y score, P-Ferritin, and dietary iron intake. Because of the non-normal distribution, P-Ferritin and dietary intake of iron were dichotomized by the median value (P-Ferritin median = 128.7 µg/L and dietary iron intake median = 9.77 mg/day).
To check whether the variables that significantly differed between MCI and NC independent of age, sex, and UPDRS III, logistic regression models adjusted for age, sex, and UPDRS III were performed. To investigate the specific cognitive domains (i.e., the association with the variables differing between patients with MCI and patients with NC), partial correlations was used with corrections for age, sex, and UPDRS III with the biochemical assessments and merged scores for the separate cognitive domains.
The Cox proportional hazards model was used to study the association between biochemical assessments at baseline and the development of PDD. Variables associated with MCI were included in Cox-regression models, first univariate, and then multivariate adjusted for age, gender, UPDRS III at baseline, and finally MCI at baseline was added.
The program Predictive Analytics Software (SPSS Statistics, version 24 SPSS Inc., Chicago IL, USA) was used for the analysis.



Baseline data

Non-motor and motor functions assessed at baseline for patients with PD (n=73) and for patients with MCI (n=30) and NC (n=43) are presented in Table 1. At baseline, MCI was more prevalent in males than in females and was associated with older age, lower level of education, and higher UPDRS III score. Patients with MCI had higher daily intake of iron and lower MNA score, P-Albumin, and P-Fe before adjusting for age, sex, and UPDRS III (Table 2). After adjusting, the OR for having MCI was still significant for P-Albumin, P- Fe and daily intake of iron but not for MNA score (Exp B: 95% CI = 0.799 (0.672-0.950), p = 0.011), P-Fe (Exp B: 95% CI = 0.854 (0.744-0.980), p = 0.025), dietary iron intake (Exp B: 95% CI = 4.425 (1.54-18.9) p = 0.019), and MNA score (Exp B: 95% CI = 0.79 (0.984-1.125, p = 0,057, respectively) (Table 2). Biochemical and nutritional assessments for males and females, including variables for iron homeostasis, are presented in Table 3. Males had higher P-Ferritin and dietary iron intake than females. No other differences indicate sex dependent disturbed iron homeostasis and nutritional status.


Table 2 Baseline variables (mean±sd) used to assess iron status in PD patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). The level of significance from the logistic regression with adjustments for age, sex, and UPDRS III are presented in the right column

Table 2
Baseline variables (mean±sd) used to assess iron status in PD patients with Mild Cognitive Impairment (MCI) and Normal Cognition (NC). The level of significance from the logistic regression with adjustments for age, sex, and UPDRS III are presented in the right column

* Plasma ferritin and dietary iron intake were dichotomized to over and under median value (median=128.7 μg/L and median = 9.77 mg/day respectively) As seen in table 3. Abbreviations: TrF % = S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1); MNA = Mini Nutritional Assessment.


Correlations between P-Albumin and neuropsychological tests

Composite scores of working memory correlated with P-Albumin levels (r = 0.452, p < 0.001) and P-Ferritin levels (r=270, p=0.025).   Both correlations were stronger for males than females: P-Albumin (male; r = 0.549, p < 0.001 and female r = 0.331, p = 0.069 (Figure 1), P-Ferritin (male; r = 0.413, p = 0.01 and female r = 0.212, p = 0.252)  Composite scores of episodic memory correlated with P-albumin (r = 0.253, p = 0.036). After adjusting for age, gender, and UPDRS III score in partial correlations, the positive association between composite score of working memory and P-Albumin (r = 0.346, p = 0.004) and P-Ferritin (r = 0.309, p = 0.012) remained significant.

Table 3 Baseline variables in mean±sd and for min-max used to assess iron status in patients with PD

Table 3
Baseline variables in mean±sd and for min-max used to assess iron status in patients with PD

* Plasma ferritin and dietary iron intake were dichotomized to over and under median value (median=128.7 µg/L and median = 9.77 mg/day respectively); Abbreviations: TrF % = S-Fe [µmol/L] x 100 / (S-Transferrin [g/L] x 25.1); MNA = Mini Nutritional Assessment.


Figure 1 P-Albumin levels correlated with composite score of working memory and were stronger for males than females (male: r = 0.549, p < 0.001 and female: r = 0.336, p = 0.064)

Figure 1
P-Albumin levels correlated with composite score of working memory and were stronger for males than females (male: r = 0.549, p < 0.001 and female: r = 0.336, p = 0.064)


Cox regressions in prediction of PDD

Results from Cox regression analysis are shown in Table 4. Lower baseline P-Fe (µmol/L) and P-Albumin (g/L) levels increased the risk of PDD at follow-up in univariate models. In models controlling for age, sex, and UPDRS III, lower levels of P-Fe significantly increased the risk of PDD (HR (95% CI) = 0.85(0.76-0.94), p = 0.002). Adding MCI to the model did not affect the higher risk of PDD with lower P-Fe levels (HR (95% CI) = 0.87(0.78-0.98), p = 0.02).

Table 4 Results from Cox regression (HR 95% CI) with Dementia as outcome variable and nutritional variables as explanatory included are presented with bivariate and multivariate calculations

Table 4
Results from Cox regression (HR 95% CI) with Dementia as outcome variable and nutritional variables as explanatory included are presented with bivariate and multivariate calculations

*Adjusted for age, sex, and UPDRS III. ** Adjusted for age, sex, UPDRS III, and MCI; Iron intake was dichotomized to over and under median value (9.77 mg/day); Abbreviations: MNA = Mini Nutritional Assessment.



The main finding from our study is that low levels of P-Fe were associated with MCI at time of diagnosis and increased risk of dementia over 10 years, while neither intake of iron, MNA-score, nor P-Albumin predicted dementia at follow-up. In addition, significantly lower levels of P-Albumin and lower score on Full MNA, indicating risk of malnutrition, and higher dietary intake of iron were seen in patients with PD-MCI at time of diagnosis. With adjustments for age, sex, and UPDRS III, the difference was maintained only for P-Albumin and dietary intake of iron.

Lower levels of P-Albumin, P-Fe, and Full MNA score at diagnosis for patients with MCI indicate malnutrition, which may have had its origin years prior to diagnosis and first symptoms. An association between MNA score and MCI in older in-patients (29) and between MNA score and disease severity and progress of disability in patients with PD has been reported (30,31). Nutritional status may be affected by several of the disease-related measurements such as ADL, UPDRS, and medication.
Used at baseline to assess malnutrition, the MNA score was lower in patients with MCI compared to patients with NC, but it did not predict PDD at follow-up. Different components of nutritional status besides results from a screening test may have importance when focusing on risk of dementia progression (32). However, MNA score has been shown to correlate with P-Albumin and dietary intake of iron (33). Being malnourished and having MCI may also have contributed to low P-Fe levels and may be one of several components of nutritional status that can influence progress to PDD. Difficulties in eating abilities and cutting food, often reported in PD patients, can result in a low intake of nutrients and energy. Age, disease, and sex-related factors also contribute to the consequences of malnutrition. In addition to finding predictors for different disease outcomes at the time of diagnosis, we also need to focus on finding PDD predictors already in the prodromal phase of PD.
In the present study, P-Albumin was significantly lower in patients with MCI than in patients with intact cognition at baseline. Albumin has previously mostly been associated with mortality and aging (34,35,36), although a handful studies have found an association of low levels of P-Albumin with cognitive decline (37,38). The different P-Albumin levels between MCI and NC were still significant after controlling for age and disease severity, which indicates that P-Albumin has a specific connection to cognitive decline. Also, the correlation between P-Albumin and P-Ferritin within normal limits and working memory was stronger in men than in woman, which suggests a sex difference for the impact of P-Albumin and P-Ferritin levels on working memory. No studies have reported this association before. As several comparisons were performed, the results may be spurious. Had we applied Bonferroni correction, only P-Albumin would have been considered significantly different between MCI and NC. Frangos et al. (2016) concluded that both age and disease contribute to low albumin, which could explain low haemoglobin levels in malnourished associated anaemia in very old hospitalized elderly (39). The baseline levels of P-Albumin and MNA score indicate an early association with cognitive decline in patients with PD in our study population.
Haemoglobin analysis was not performed on the same occasion/visit with blood sampling and assessment of malnutrition, limiting the possibility to assess anaemia. However, iron deficiency may be important for cognitive function independent from anaemia. Yavuz et al. (2012) studied geriatric patients (mean 72 years of age) and concluded that iron levels and Trf % independently correlated with MMSE. In that study, patients with dementia had low Trf % and a low MMSE associated with iron deficiency (11). Mean levels for P-Transferrin increase to compensate for low P-Fe and increased need, but in our study mean levels for P-Transferrin decreased with malnutrition. P-Fe is transported with transferrin, and about 30-40% of this capacity is used dependent on age and sex and increases after the age of 70 years (40,41). Besides being an iron transporter, P-Transferrin is a marker for nutritional status (42,43). By a shorter half-life than albumin, transferrin may be a strong marker for protein energy malnutrition within days to weeks.
Iron deficiency may affect dopamine metabolism (44,45), and dysregulation of iron metabolism has been described as a risk factor for PD (46). Iron homeostasis is reported to be important for cognition (47). Cognitive impairment has been reported among elderly with iron deficiency and malnutrition (11,12).  Iron deficiency in adults and elderly indicates that age and sex may have contributed to hypo-metabolism that might have resulted in early dementia in Parkinson’s disease (48). In the present study, age was associated with both MCI at baseline and with increased risk for dementia over 10 years. The vicious circle with ageing, malnutrition, and cognitive decline may be even stronger in PD patients due to disease-related disturbances than in a non-PD elderly population. A low bioavailability of iron in the intestine (the main cause of iron deficiency, at least among elderly) could have generated the low P-Fe in the present population of patients, for example, due to gastrointestinal disturbances like gastro pares and achlorhydria (49). The level of P-Fe varies from day to day and low levels indicate either low intake or malabsorption. The risk of MCI, associated with either high intake of iron or low plasma Fe, indicate the importance of intestinal function for maintaining iron homeostasis. A high intake of iron may affect bioavailability of other minerals and thereby contribute to deficit cognition. To study influence from dietary intake, more information on nutrient density in general and individual energy intake are needed together with data on intestinal function and medication. Reporting dietary intake may also have been affected by the level of cognitive ability.



Our results indicate that low P-Fe was associated with MCI at baseline and increases risk for dementia up to 10 years after diagnosis of PD. Low P-Albumin and disturbed cognition in PD may influence the progression to dementia and be a sign of protein energy malnutrition. High intake of iron increased the risk of MCI at baseline but did not show any effect on PDD risk. We suggest that low P-Fe in our sample might be related to a disturbed regulation, including intestinal absorption in iron metabolism as well as malnutrition.


Funding: This study was funded by The Swedish Parkinson Foundation (Svenska Parkinsonstiftelsen), Swedish Parkinson foundation, Neuro Sweden, The Swedish Parkinson Disease Association, The Swedish Medical Research Council and Västerbotten County Council (ALF).

Conflict of interest: The authors declared that they had no conflict of interests.

Ethical Standard: The study was approved by the Ethics Committee of the Faculty of Medicine at Umeå University. Written, informed consent was obtained from all participants.



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V. Ferri Ross Perucha1, R. de Cássia de Aquino1, N. Gaspareto1, E.M. Guerra-Shinohara2, P. Mendonça da Silva Amorim2, V. d’Almeida3


1. Postgraduate Program in Science Aging, São Judas Tadeu University- USJT, São Paulo-SP, Brazil; 2. Department of Clinical Analyses and Toxicology, School of Pharmaceutical Science, University of São Paulo- FCF-USP – São Paulo-SP, Brazil; 3. Laboratory for Inborn Errors of Metabolism, Federal University of São Paulo-UNIFESP – São Paulo-SP, Brazil

Corresponding Author: Viviane Ferri Ross Perucha, Universidade São Judas Tadeu, R. Taquari, 546 – Mooca, São Paulo/SP, CEP 03166-000, Brazil, +55 11 2799-1677, viviperucha@gmail.com.

J Aging Res Clin Practice 2017;6:48-55
Published online March 22, 2016, http://dx.doi.org/10.14283/jarcp.2017.5



Background: An increased risk of cognitive decline in the elderly with B12 deficiency has been associated with excessive synthetic folic acid in food fortification and supplements. Objectives: To assess the dietary folate and folic acid intake from food fortification, as well as serum vitamin B12, folate, iron, and homocysteine concentrations among the elderly and their relationships with cognitive changes. Design: Cross-sectional, observational study. Setting and Participants: Community-dwelling elderly (N = 40), predominantly female (90%), with an average age of 69 years. Measurements: Dietary intake information was collected using four 24-hour dietary recalls, adjusted for iron and folic acid in fortified flour and supplements. Serum vitamin B12, B6, folate, iron, and homocysteine concentrations were determined. Cognitive function was assessed using the Mini-Mental State Examination, adjusted for educational level. Results: Possible serum vitamin B12 deficiency (<258 pmol/L) was present in 5% of the elderly participants, while 27.5% had possible functional deficiency (<400 pmol/L). No serum folate deficiency (<6.8 nmol/L) was observed; however, 15% had possible deficiency (<13.6 nmol/L), and 7.5% had supraphysiological levels. Hyperhomocysteinemia (≥15 µmol/L) was present in 65% of the sample. Almost half of the participants (47.5%) showed cognitive impairment. There were no significant relationships between the Mini-Mental State Examination results and the B12, folate, iron, and homocysteine concentrations. However, the participants with serum vitamin B12 levels <400 pmol/L tended to have poorer Mini-Mental State Examination scores, which were related to older age (P = 0.045) and changes in the oral cavity (P = 0.034). In addition, folic acid consumption was inversely related with serum vitamin B12 levels (P = 0.030). Macrocytosis was not observed. Conclusions: Although Mini-Mental State Examination-assessed cognitive impairment was not related with the investigated biochemical variables, increased folic acid consumption seems to have a negative impact on vitamin B12 metabolism; therefore, fortification may be contributing to functional disability and masking hematological signs in the elderly.

Key words: Cobalamin, folate, synthetic folic acid, homocysteine, cognition.



The longevity of the Brazilian population has steadily increased in recent decades, following the global trend, and projections for 2050 place Brazil among the countries with the largest elderly populations in the world (1). However, longevity is not always associated with healthy aging. Micronutrient deficiencies, which are exacerbated by the presence of disease, and the use of multiple medications, are common among the elderly (2).
Aging-related vitamin B12 (cobalamin) deficiency is particularly common, in both developed and developing countries. Vitamin B12 malabsorption is a principal cause, affecting 30–40% of the elderly (3). The etiologic factors include atrophy of the gastric mucosa and reduced secretion of hydrochloric acid and intrinsic factor, which are affected by atrophic gastritis, pernicious anemia, and Helicobacter pylori infection as well as antacids and diabetes medications, such as omeprazole and biguanides, respectively (4).
The clinical manifestations of vitamin B12 deficiency range from asymptomatic to very severe cases. It is generally characterized by megaloblastic anemia associated with neuropsychiatric symptoms, which may be irreversible (3,4). In addition to neuropathy, memory deficits, cognitive impairment, depressive disorders, dementia, Alzheimer’s disease, and Parkinson’s disease are also reported (5).
The methylation metabolic pathway interrelates the metabolism of vitamin B12, folate, and homocysteine (Hcy) (3,6); based on disruption of this pathway, epidemiological studies have associated an increased risk of cognitive decline in vitamin B12-deficient elderly people with consumption of high doses of synthetic folic acid (FA), used in flour fortification and supplements (7, 8). The increasing cognitive decline and demyelination could be explained by the “methyl trap” hypothesis. This hypothesis states that vitamin B12 deficiency results in a state of hypomethylation caused by the bound 5-methyltetrahydrofolate, which cannot be recycled into tetrahydrofolate, whose reaction would be mediated by the enzyme methionine synthase (responsible for the conversion of Hcy to methionine) that is dependent on vitamin B12 as a cofactor. In addition, the retained 5-methyltetrahydrofolate cannot be used in DNA synthesis, resulting in symptoms identical to that of the anemia (megaloblastic) that occurs in cases of folate deficiency. This condition can be aggravated by high doses of FA, which tend to correct the anemia but not the neurological symptoms (3, 6). It is also suggested that the oxidative effects of non-metabolized FA prevent the action of vitamin B12 in cytosolic and mitochondrial compartments; this explains the increase in both Hcy and methylmalonic acid (MMA) and characterizes the worsening of functional vitamin B12 deficiency (7, 9). In animal models, negative metabolic effects associated with excess FA seem to be influenced by genetic polymorphisms of enzymes related to methylation such as MTHFR 677C>T (10), which is also associated with hyperhomocysteinemia and neurological disorders in humans (11).
Another concern with FA fortification is the presence of cognitive impairment in elderly patients with normal, or close to normal, serum vitamin B12 values, accompanied by an increase in the level of functional biomarkers (12). The effect of FA in reducing macrocytosis, which may mask the hematological signs of vitamin B12 deficiency, has also been reported (8, 12, 13).
Studies also indicate that excess folate might facilitate the progression of pre-neoplastic lesions, increasing the risk of cancer in humans (14). Collectively, these results have stimulated discussions of the undesirable effects of mandatory FA fortification in the general population and elderly, which are in contrast to the potential benefits of fortification for women of childbearing age, specifically related with risk reduction for neural tube defects in the fetus (6, 14).
Given that vitamin B12 deficiency is a common problem with aging (3) and due to the policy of fortifying flour with FA and iron in Brazil (15), this study aimed to assess dietary folate and FA intake and serum concentrations of vitamin B12, vitamin B6, folate, iron, and Hcy as well as their relationships with cognitive impairment in community-dwelling elderly.



Study Population

We included elderly participants (aged ≥60 years) of extension projects for seniors at the São Judas Tadeu University (USJT), a private Brazilian institution, located in São Paulo-SP. All participants were informed of the objectives and procedures of the research and the risks and benefits described in the Terms of Consent Form. The project was approved by the Research Ethics Committee (REC) of USJT, protocol 096/2011. Data collection was conducted between February and July 2012.

Nutritional and Anthropometric Assessments

The initial interview collected personal details, socio-demographic information, current and previous clinical history, medications in use, general health conditions, body weight history, physical activity, general data on food, and a 24-hour dietary recall (R24h). In addition, an anthropometric assessment was conducted by qualified nutritionists using recommended techniques and consisted of body weight, standing height, body mass index (BMI), and waist circumference (WC).
Nutritional status was classified using BMI and was calculated using the proposal of the Pan American Health Organization (16). The World Health Organization (WHO) waist circumference cutoff points for adults were used (17), because there are no reference values for the elderly.
Information about changes in the oral cavity and tongue was collected, because these are related with vitamin B nutritional status, especially that of vitamin B12 and folate (18).

Assessment of Food Intake

Four R24h were performed, the first during the initial interview and the other three on other days of the week at average intervals of 10 days and including a weekend day (Sunday). Food consumption was collected with the four R24h using usual measures (e.g., measuring cup, bowl) and converted to grams/mL with the aid of usual measure tables or guides; then, food intake was calculated according to energy and the macro- and micronutrient composition. The composition and dosage of supplements used by the participants were determined using the labels or prescriptions, and the amounts for those containing vitamin B12, vitamin B6, or FA were added to the intake values. To adjust for bioavailability, the FA supplement values, in µg, were converted to dietary folate equivalents (DFEs), in µg, by multiplying by a conversion factor of 1.7 (19).
To evaluate food intake, a database with 376 foods was created, based on the 2011 Brazilian Table of Food Composition (TACO), 4th edition (20), and the USDA on-line version (Release 24) (21) was used to adjust the levels of vitamin B12 and folate, because a national composition table that includes these two nutrients in national foods is not available. Also, it was necessary to adjust the folate and iron values in 48 foods produced with fortified flour, in accordance with the mandatory fortification policy for flour in Brazil (RDC 344); the following amounts were added for wheat flour, corn flour, corn meal, and corn flakes: 4.2 mg iron/100 g food and 150 µg folic acid/100 g food (15). Total folate was calculated as the sum of natural folate (dietary) and the synthetic form (FA present in foods and/or supplements). The principal nutrients of interest in the research, such as vitamin B12, vitamin B6, folate, FA, and iron, were adjusted for energy intake (per 1000 kcal).

Biochemical Evaluation

Blood collection and preparation of the biological material were performed in the laboratory of the Center for Pharmaceutical Studies at the USJT. The technical and operational recommendations for collection, storage, and transport were followed. Blood collection was performed in the morning after a minimum fasting period of 10 hours.
The serum concentrations of folate and vitamin B12 were determined using the microbiological method, with strains of Lactobacillus casei and Lactobacillus leichmannii, respectively. Plasma Hcy levels were determined using high performance liquid chromatography (HPLC) with fluorimetric detection and isocratic elution. Plasma vitamin B6 levels were determined using HPLC with ultraviolet detection and isocratic elution. A complete hemogram was performed on whole blood with EDTA anticoagulant using manual analysis of hematologic indices and employing blood extension and the Panoptic staining method (New Prov®, Pinhais/PR, Brazil). Glucose was measured in plasma with fluoride anticoagulant, and the other biochemical tests (lipid profile, kidney function, and liver function) were conducted using serum samples. For general biochemical analysis, the Bio-2000 model (Bio-Plus®, Barueri/SP, Brazil) and specialized kits from Doles® (Goiania/GO, Brazil) were used. The Iron kit for the modified Goodwin method was used for serum iron.
To analyze the biochemical variables, cutoff points described in the literature were adopted: vitamin B12, possible deficiency (<258 pmol/L) (22) or possible functional deficiency (<400 pmol/L) (23); serum folate, deficiency (<6.8 nmol/L or <3 ng/mL), possible deficiency (<13.6 nmol/L or <6 ng/mL), or supraphysiological (>45.33 nmol/L or >20 ng/mL) (24); vitamin B6, deficiency (<20 nmol/L pyridoxal phosphate) (19); and hyperhomocysteinemia (Hcy ≥15 μmol/L). There is no consensus in the literature regarding the cut-off points of Hcy for the elderly (usually ≥12–15 μmol/L). The higher limit adopted also considered the acceptable Hcy level for elderly exposed to FA fortification and/or supplementation (25).
For the remaining biochemical markers (serum iron, blood count, lipid profile, and kidney and liver function), cutoff points suggested by the laboratory were adopted. Anemia and macrocytosis were determined using hemoglobin levels (women: <11.7 g/dL; men: <13.5 g/dL) and mean corpuscular volume (women: > 100fL; men: >95 fL), respectively. Serum creatinine levels were used to assess kidney function.

Evaluation of Cognitive Function

The Mini-Mental State Examination (MMSE) was used to evaluate cognitive function. Because education and age are very influential on MMSE scores, the Brazilian version was used, with possible scores of 0–30 points (26).

Statistical Analysis

A statistical significance of 5% was adopted, and SPSS version 17.0 (SPSS Inc., Chicago, IL) was used for all analyses. Quantitative data are described as the arithmetic mean and standard deviation (SD), median and interquartile range (equivalent to the 25th and 75th percentiles of the median values), and/or categorized as the cut-offs or adopted reference standards. Qualitative data are categorized and described according to the frequency distribution percentage.
Normality was verified using the Skewness-Kurtosis test. Pearson correlation tests were performed for quantitative variables with a normal distribution, and Spearman correlation tests were used for the variables with an asymmetric distribution. The Student’s t test was used to analyze differences between variables with normal distributions, and the Mann-Whitney test was used to analyze differences between variables with an asymmetrical distribution.



General Characteristics of the Elderly Participants

The sample included 40 elderly people (90% women), with a mean age of 68.97 years (SD ± 6.51). All were physically independent and participated in extension projects for seniors at a university. Educational level was diverse, with 65% of participants completing up to 8 years of education. The most common clinical conditions were hypertension, diabetes, dyslipidemia, and metabolic syndrome. Almost half of the participants were overweight or obese (47.5%), and the majority (75.0%) had a considerably increased metabolic risk (Table 1).
Clinical signs involving the gastrointestinal tract, such as changes in the oral cavity or tongue, were cited by almost half of the population (45%) (Table 1), and 15% reported changes of the tongue (burning, cracking, pain, redness, paleness, or smooth texture). The use of vitamin B12 or FA supplements was reported by 5% of the participants, and the use of vitamin B6 supplements was reported by 7.5% of the participants.

Table 1 Primary general characteristics of the elderly sample (São Paulo, 2013)

Table 1
Primary general characteristics of the elderly sample (São Paulo, 2013)

Biochemical Evaluation

The biochemical analyses showed that 5% of the population had possible B12 deficiency (<258 pmol/L), and 27.5% had possible functional deficiency (<400 pmol/L). Regarding folate, none of the participants were classified as deficient (<6.8 nmol/L or 3 ng/mL), but 15% had a possible deficiency (<13.6 nmol/L or <6 ng/mL), whereas 7.5% had supraphysiological levels (>45.33 nmol/L or >20 ng/mL). Adequate plasma vitamin B6 and iron levels (>30 nmol/L and 60–160 μg/dL, respectively) were found in almost the entire sample (97.5% and 95%, respectively). Regarding Hcy, high serum levels (≥15 μmol/L) were found in 65% of the participants. Anemia, macrocytosis, and renal dysfunction were not present for any of the participants (data not shown).

Relationships with MMSE

The average MMSE score was 26.2 (SD ± 1.7) points, and almost half of the participants (47.5%) had cognitive impairment, after adjusting for education (Table 1). There were no significant differences in serum vitamin B12, folate, iron, or Hcy levels between the MMSE classifications (P ≥ 0.05). However, participants with low cognitive performance had lower serum vitamin B12 levels (457 vs 487 pmol/L) and lower serum folate levels (24.7 vs 26.8 nmol/L) than those with normal cognitive performance (Table 2). There were also no differences in plasma vitamin B6 levels between MMSE classifications (P = 0.797; data not shown).

Table 2 Median serum or plasma vitamin B12 (pmol/L), folate (nmol/L), homocysteine (µmol/L), and iron (µg/dL) levels and their relationships with the Mini-Mental State Examination (MMSE) classification of elderly participants (São Paulo, 2013).

Table 2
Median serum or plasma vitamin B12 (pmol/L), folate (nmol/L), homocysteine (µmol/L), and iron (µg/dL) levels and their relationships with the Mini-Mental State Examination (MMSE) classification of elderly participants (São Paulo, 2013).

(1) Student t tests were used to compare values for variables with a normal distribution (2) Mann-Whitney tests were used to compare values for variables without a normal distribution; IQR, interquartile range (25th percentile to 75th percentile).


There were also no significant differences in the MMSE score between the classifications of serum vitamin B12, folate, or Hcy concentration. However, the mean MMSE score was almost one point less (25.45 vs 26.59 points) among those with possible functional vitamin B12 deficiency (<400 pmol/L) than in those with a better B12 status (≥400 pmol/L), indicating a trend. In addition, participants with possible functional deficiency were older than those with better vitamin B12 status (72 vs 67 years; P = 0.045; Table 3). Complaints of oral cavity changes were more frequent (72.7% vs 34.5%) among those with serum B12 levels <400 pmol/L than those with better vitamin B12 status (P = 0.034; data not shown).

Table 3 Relationships between serum or plasma vitamin B12 (pmol/L), folate (nmol/L), and homocysteine (µmol/L) levels and median Mini-Mental State Examination (MMSE) score and age of the elderly sample (São Paulo, 2013)

Table 3
Relationships between serum or plasma vitamin B12 (pmol/L), folate (nmol/L), and homocysteine (µmol/L) levels and median Mini-Mental State Examination (MMSE) score and age of the elderly sample (São Paulo, 2013)

(1) Student t tests were used to compare values for variables with a normal distribution (2) Mann-Whitney tests were used to compare values for variables without a normal distribution; IQR, interquartile range (25th percentile to 75th percentile).


Regarding folate, participants with possible deficiency (<13.6 nmol/L) also had an MMSE score around one point higher (27.17 vs 26.12 points) and were older (70.50 vs 67.00 years) than those with a higher folate level (≥13.6 nmol/L), although these differences were not significantly different (Table 3).
Plasma Hcy levels were not related with MMSE scores (P ≥ 0.05; Tables 2 and 3). Participants with plasma Hcy levels ≥15 μmol/L were significantly older than those with lower Hcy levels (<15 μmol/L; 69 vs 67 years; P ≥ 0.05; Table 3).
Age was positively correlated with Hcy levels (r = 0.427, P = 0.006) and negatively correlated with serum folate levels (r = -0.336; P = 0.034) (data not shown).

Figure 1
Median consumption of total folate (µg Dietary Folate Equivalent [DFE]) or synthetic folic acid (µg) from fortification, reported as raw data (A) and adjusted for energy (1000 kcal) (B), and their relationships with the Mini-Mental State Examination (MMSE) classification of the elderly participants (São Paulo, 2013)

Figure 1 Median consumption of total folate (µg Dietary Folate Equivalent [DFE]) or synthetic folic acid (µg) from fortification, reported as raw data (A) and adjusted for energy (1000 kcal) (B), and their relationships with the Mini-Mental State Examination (MMSE) classification of the elderly participants (São Paulo, 2013)

(1) Student t tests were used to compare values for variables with a normal distribution (2) Mann-Whitney tests were used to compare values for variables without a normal distribution. Total folate was calculated as the sum of that consumed via the diet and fortification.

Folic Acid Intake and Relationships between Folate and MMSE scores and Vitamin B12 Concentrations

Considering 1000 kcal-adjusted values (Fig. 1-B), both the average total folate intake (261.3 ± 43.1 vs 256.0 ± 49.9 µg DFE; P = 0.723) and FA intake from fortification (70.6 ± 23.4 vs 60.7 ± 27.3 µg; P = 0.224) were higher, but not significantly different, among participants with lower MMSE scores; however, the respective non-adjusted raw data (Fig. 1-A) were significantly different for FA intake (73.9 ± 27.3 vs 119.0 ± 23.4 µg; P = 0.047), and a trend was observed for total folate intake (382.5 ± 108.2 vs 442.7 ± 78.0 µg DFE; P = 0.053).

Figure 2
Pearson correlations between serum vitamin B12 levels (pmol/L) and synthetic folic acid1 (µg) (A) and total folate intake2 (µg dietary folate equivalent [DFE]) (B) of the elderly sample (São Paulo, 2013)

Figure 2 Pearson correlations between serum vitamin B12 levels (pmol/L) and synthetic folic acid1 (µg) (A) and total folate intake2 (µg dietary folate equivalent [DFE]) (B) of the elderly sample (São Paulo, 2013)


(1) Fortification, adjusted for energy intake (1000 kcal) (2) Diet + fortification, adjusted for energy intake (1000 kcal)

FA intake from fortification was inversely correlated with serum vitamin B12 levels (r = -0.341; P = 0.030; Fig. 2-A). The relationship between total folate intake and serum vitamin B12 levels was not statistically significant (r = -0.250; P = 0.120; Fig. 2-B). Similarly, FA intake from fortification and supplements was inversely correlated with serum vitamin B12 levels (r = -0.344; P = 0.030), while total folate intake was not significantly associated with vitamin B12 levels (r = -0.218; P = 0.176; data not shown).



Micronutrient status can affect cognitive function at any age. In the elderly, low serum B vitamin levels and high Hcy concentrations can influence memory and are considered risk factors for mild cognitive impairment, vascular dementia, and Alzheimer’s disease (5, 27). Of the B vitamins that may affect Hcy level and neurological function (11, 27) and were measured in the present study, the rate of inadequacy was lowest for vitamin B6 (2.5%); this is not surprising given that the subjects were active non-institutionalized elderly. In addition, vitamin B6 levels and MMSE classification were not related.
Consistent with the literature, where it is estimated that vitamin B12 deficiency affects 5–25% of the elderly (3), 5% of the sample in the present study had low serum vitamin B12 levels (<258 pmol/L), and the levels for 27.5% of the sample were in the at-risk range for functional deficiency (<400 pmol/L). The higher cutoff point for vitamin B12 was adopted as an alternative in the absence of specific functional biomarkers, such as MMA and holotranscobalamin (holo-TC), based on observations that levels <400 pmol/L are associated with elevated MMA and Hcy levels (23), and consequently, with the risk of cognitive decline in elderly people (12).
The present study found evidence of a beneficial effect on cognitive function with the maintenance of higher serum vitamin B12 levels. There was an observed trend in MMSE scores, with a difference of approximately one point in the MMSE based on a serum vitamin B12 level cut-off ≥400 pmol/L (P = 0.075). Among the elderly in the Framingham Heart Study, lower B12 concentrations (<257 pmol/L) were related with a faster rate of decline in the MMSE score (0.35 points/year) over 8 years of follow-up, although no association was observed at baseline in the first cross-sectional analysis (28). Another result observed in the present study was that elderly subjects with functional vitamin B12 deficiency (<400 pmol/L) were older and more frequently reported alterations in the oral cavity, which can be related with anemia due to vitamin B12 or folate deficiency (18).
In the present study, although no statistically significant differences were observed between serum folate levels and MMSE classification, recent evidence suggests that high levels of folate, from FA consumption, increase the risk of cognitive decline in elderly people with low serum vitamin B12 levels (7,8,29). The synthetic form of the vitamin has an approximate 80% bioavailability (19) and is slowly metabolized in humans (6), which may explain the results of the present study, including an absence of classic deficiency, and supraphysiological levels in 7.5% of the sample. The mean serum folate level was 29.12 (± 21.62) nmol/L; the average total folate intake (628 ± 1266 μg/day) was higher than the Recommended Dietary Allowance (≥400 μg/day) (19). According to a recent review (30), the mean serum folate level among elderly Brazilians in the post-fortification period ranged from 24.7 (± 6.9) to 28.6 (± 11.3) nmol/L; consumption was not investigated.
Further analysis of food consumption in the present study provided another important result that agrees with growing evidence on the risks of fortification—isolated FA from fortification and/or supplements was inversely correlated with serum vitamin B12 levels, which could be interpreted as an inductive effect of vitamin B12 deficiency. Recent studies in the US with the elderly population exposed to FA fortification observed that the combination of low vitamin B12 levels (<148 pmol/L or MMA >210 nmol/L) and high folate levels (>59 nmol/L) increased the risk of cognitive impairment by 5 times (7).
Corroborating these findings, Morris et al. (8) evaluated the impact of non-metabolized FA (as a biomarker) on the cognitive function of elderly in the NHANES in the post-fortification period and found that the simple presence of circulating non-metabolized FA was related with poorer cognitive performance in elderly people with vitamin B12 deficiency. In the present study, despite greater FA consumption among older people with a low MMSE score, the difference was no longer statistically significant after adjustment for energy intake (per 1000 kcal). FA intake from both fortification and supplements was 239.10 μ/day, similar to the 280 μ/day reported by Morris et al. (8), which was associated with the presence of the non-metabolized form in the blood.
Conflicting results exist for countries that have opted for voluntary fortification; there was no effect among the British elderly (31), while there was a nearly 3.5-time greater risk of cognitive decline, as assessed by the MMSE, in elderly Australians (29). Conversely, re-enforcing the benefits of food-based, non-synthetic folate, Doets et al. (32) observed a positive association between plasma folate levels and cognitive performance among elderly Norwegians not exposed to fortification. This was probably due to the low prevalence of vitamin B12 deficiency and supraphysiological folate levels, attributed to the low use of supplements by the population.
Studies also suggest that excess FA can induce functional vitamin B12 deficiency, as evidenced by increases in Hcy, MMA, and holo-TC (7,9,12) that are associated with cognitive impairment among elderly Americans (7). Despite an increase in biomarkers, no relation with MMSE was observed in a cohort of elderly Latinos, potentially owing to the small subgroup of individuals with both high serum folate levels and vitamin B12 deficiency (33). In the present study, the sample size also compromised our ability to detect significant relationships. However, if we disregard the MMA levels, given that almost one third of the patients was at risk of functional B12 deficiency (<400 pmol/L), it is possible that excess FA may have contributed to the high frequency (65%) of hyperhomocysteinemia.
The reported influence of Hcy level on cognitive function was not observed in the present study. High Hcy levels, at levels that affect memory function, are associated with low folate status, a finding that has become uncommon in post-fortification studies. Furthermore, a relationship with a decrease in MMSE has been more common in longitudinal studies among individuals with lower scores and of older age (27).
The significant elevation in serum folate in the Brazilian population after fortification (30) could also explain the absence of macrocytosis in the present study sample, considering that no change was observed in mean corpuscular volume. Similar results were observed in other countries that adhered to fortification (8,13,34) and also among elderly Brazilians, in whom macrocytosis and folate deficiency were not detected despite vitamin B12 deficiency in 11%, evaluated using MMA (35). This supports the hypothesis that FA fortification may mask the hematological signs of vitamin B12 deficiency (12).
Based on this evidence, the Institute of Medicine recommends that American adults aged ≥50 years follow the dosage recommendations for synthetic replacement of vitamin B12 (19). There is still speculation as to whether the joint fortification of vitamin B12 and FA minimizes the risk of cognitive impairment in the elderly population. Despite measures that are, in theory, capable of minimizing the problem, chronic exposure to non-metabolized FA is still concerning, without an understanding of its potential long-term damage to the body (6,14).
Given the limitations of the present study, such as its cross-sectional design, sample size, female predominance, and absence of specific functional markers for vitamin B12, it was not possible to reproduce the same relationships as those identified in American population studies. Despite the limitations, the results support the risks of FA intake on B12 status in the elderly that are suggested in the literature. The MMSE is commonly used as a global assessment method of cognitive function, and the use of the Brazilian version, adjusted for education level, was considered more appropriate for the present sample. One strength in the evaluation of FA consumption was the use of four 24-hour dietary recalls and the adjustment for FA quantities established for fortification in Brazil, in addition to the evaluation of serum folate levels.
In conclusion, there were no significant relationships between the investigated biochemical variables (B12, folate, Hcy, and iron) and the MMSE results. However, despite the observation of serum vitamin B12 deficiency in only 5% of the sample, using the <400 pmol/L cutoff point, the levels for 27.5% of the elderly were in the range for a risk of functional deficiency; these participants tended to have poorer MMSE scores and to be older. FA consumption had a negative influence on serum vitamin B12 levels and explained the presence of supraphysiological levels (7.5%) and absence of classic folate deficiency and macrocytosis.
Collectively, these findings reinforce present data that indicate that FA may directly or indirectly worsen the mental health of the elderly and the importance of maintaining good B12-related nutritional status among the elderly receiving FA fortification or supplementation. Given the seriousness of the evidence, a thorough investigation is required with representative samples of the elderly population that includes functional biomarkers such as MMA and holo-TC, as well as non-metabolized FA and gene polymorphisms related with folate metabolism.


Acknowledgments: We express our gratitude to Silvana Cardoso and Roberto Ferraboli for their help collecting and analyzing the blood samples. We would like to thank Karen Barbosa Müller for their comments and suggestions in the preparation of this article. We also thank the team of Projeto Senior para a Vida Ativa and gerontology and psychology clinic of São Judas Tadeu University for their help conducting the neuropsychological tests.

Funding: The present study was funded by the São Judas Tadeu University. All authors declare that they have no conflicts of interest. No competing financial interests exist.

Ethical Standards: This research complies with the current laws of the country in which they were performed”.



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K. Kent1, S. Roodenrys2, K.E. Charlton1, R. Richards2, O. Morgan2, H. Gilbert2


1. School of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, Australia; 2. School of Psychology, Faulty of Social Sciences, University of Wollongong, Australia

Corresponding Author: K. Kent, School of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, Australia, e-mail:kc582@uowmail.edu.au



Background: Dietary flavonoid intake and intake of flavonoid subclasses has been associated with improved cognitive performance. However, the association between flavonoid intake and cognitive performance in older adults with Alzheimer’s type dementia has not been investigated. Objectives: To estimate dietary total flavonoid intake and intake of flavonoid subclasses in older adults with Alzheimer’s type dementia and assess the relationship of flavonoid intake with measures of cognition. Design: Cross sectional analysis. Setting: Community dwelling older adults in NSW, Australia. Participants: Older adults (+65y) with mild to moderate dementia (n=49). Measurements: A 24h diet recall was collected with help from a carer and used to estimate flavonoid intake. A battery of cognitive tasks assessed cognitive performance of several cognitive domains. Results: Pearson and spearman correlation coefficients identified an association between flavonoid intake and executive function (r=0.319, p=0.025). After controlling for depression, the relationship was reduced. Conclusion: The identified association between cognitive functioning, depression and flavonoid intake in older adults with Alzheimer’s type dementia warrants further research in a larger sample.

Key words: Flavonoid, cognition, dementia.



Flavonoids are naturally occurring plant-based phytochemicals, which are abundant in the human diet. The structure and sources of flavonoids has been well established (1, 2).  Flavonoids are a subclass of polyphenols and encompass a wide group of compounds that are divided into six major classes: anthocyanidins, flavanols, flavanones, flavones, flavonols and isoflavones (1). A growing body of evidence suggests that flavonoids are non-nutritive bioactive compounds, which significantly contribute to the antioxidant activity of individual fruits and vegetables and are consequently credited with the observed health benefits (3). Flavonoids are widespread across many food sources and are found in particularly high concentrations in fruits and vegetables, wine, tea, cocoa, and soy (4). In older Australian adults, major dietary sources of flavan-3-ols and flavonols are tea (black and green) and apples; flavanones are provided by citrus fruits and juices; flavones are consumed through parsley and tomatoes; and berries and red wine provide anthocyanins (5). Isoflavones are largely provided by the consumption of soy-based products (6).
Total dietary flavonoid consumption has been association with improved cognitive performance and a preservation of cognitive function with ageing (7-9). More focussed research on specific flavonoid subclasses has revealed that the sub-groups flavanols, anthocyanins and flavanones may provide the most beneficial effects in the area of neuroprotection (10). There has been a particular focus in animal models, on the provision of anthocyanin rich foods, such as blueberries, when investigating cognitive outcomes, with promising results (11-13). Preliminary human trials have also begun to link anthocyanin-rich food consumption with improvements in cognitive outcomes (14-18).  A high consumption of total dietary flavonoids has also been linked with a reduced risk of developing a neurodegenerative disease, such as dementia (19). However, the association between flavonoid intake and cognitive performance in older adults with Alzheimer’s type dementia has not been investigated to date.
The mechanisms by which flavonoids provide neuroprotection are not well elucidated and the evidence remains largely pre-clinical. This is partially related to the quick and extensive metabolism of dietary flavonoids into metabolites with differing and largely unknown biological activities (1). In animal models, specific flavonoids including the flavanols catechin and epigallocatechin gallate (20) have been shown to reduce neuroinflammation and scavenge free radicals within the brain (2), a function which has been related to neuroprotection. Additionally, flavonoids, including the flavanone hesperitin have been shown to provide a range of positive neuronal effects to limit neurodegeneration, including a potential to protect neurons against injury and improve neuronal morphology (2, 21). Flavonoid supplementation has also been shown to up-regulate processes that promote learning, memory and cognition (1). Flavonol-rich cocoa consumption has shown to increase cerebrovascular blood flow, which is associated with improved cognition (22). Presently, it is unclear how many, or if all flavonoids exert such effects (1).
Evidence is mounting for the positive protective effects of flavonoid consumption for the development of dementia (7, 19, 23), including consumption of flavonoid rich fruits and vegetables, juices and wine (24, 25). However, it is also important to investigate the relationship between flavonoid consumption in older adults living with dementia and cognitive performance outcomes. This evidence could be utilized to indicate if dietary interventions with flavonoids may be warranted. It is well documented that older adults with dementia develop eating difficulties, resulting in low food intake, as dementia progresses (26). This can be related to a myriad of difficulties including dysphasia, lack of appetite, confusion about the need to eat and the loss of the ability to recognize food (27). The total dietary intake and significant sources of dietary flavonoids in older adults living with dementia has not been assessed and may differ from estimations for healthy adults aged 65+yrs.
The aim of this study was to estimate the total dietary intake and main sources of flavonoids in older Australian adults with Alzheimer’s type dementia and to assess the relationship between dietary flavonoid intake and cognitive performance.



This study was approved by the University of Wollongong and Illawarra Shoalhaven Local Health District Human Research Ethics Committee (HE11/175) and complied with current laws governing ethics in research. The current study analysed the baseline data of a randomised controlled trial, which investigated the impact of anthocyanin-rich cherry juice on cognitive outcomes in older adults with dementia (17)
Community dwelling older adults (65+yrs) with mild to moderate Alzheimer’s type dementia (as diagnosed by a hospital-based geriatrician) were recruited to the study from an outpatient clinic. Dietary data was collected by a trained nutritionist (KK) (with assistance and confirmation provided from a carer) from a single 24-h food recall. The dietary data was analysed using the Foodworks dietary analysis package (Xyris software, version 5, 2007, Highgate Hill, QLD, Australia) (28). As dietary data relating to flavonoid content of foods is not integrated into the Xyris software, the food items were manually cross-referenced with the USDA database for the flavonoid content of selected foods (release 3.1) (29) to estimate total flavonoid consumption and the flavonoid subclasses anthocyanins, flavones, flavanones, flavonols and flavan-3-ols. A Mini Nutritional Assessment (30) was conducted as a measure of malnutrition and Lawton’s Instrumental Activities of Daily Living Scale (31) measured functional ability. Anthropometric and demographic information, including education, was collected (Table 1), with assistance from a guardian or carer as appropriate.

Table 1 Characteristics of study participants (n=49)

Table 1
Characteristics of study participants (n=49)

Ideal BMI for adults 65y+ is 22–27 kg/m2 (13); Calf circumference and mean mid-upper arm circumference in of 29.2 in older adults; Mini Nutritional Assessment score >23.5 indicates no risk of malnutrition (14); Median maximum hand grip strength are 37.9 kg and 31.5 kg for men and women aged 50y+ (15); Lawton’s IADL scale mean score 4.3 in adults with moderate dementia (11).


A battery of cognitive assessments was administered by a single trained researcher (KK). These included measures of mood (32), verbal learning and memory (33), working memory (34), semantic memory (35), executive function (36, 37) and short-term memory (38) (Table 2).


Table 2 Cognitive instruments, domain targeted and relationship with total flavonoid intake

Table 2
Cognitive instruments, domain targeted and relationship with total flavonoid intake


Correlation is sig. at p<0.05. ** Correlation is sig. at p<0.01


To assess the relationship between flavonoid intake and cognitive performance, bivariate correlations with Pearson and Spearman coefficients (as appropriate) were performed and then repeated after controlling for depression, as measured by the Geriatric Depression Scale (GDS) (32). Multiple regression analysis was performed to confirm the effect of flavonoid intake on cognitive outcomes that were identified as significant by the correlations, with age and education included in the models as covariates.



Forty-nine participants volunteered to take part in the study; their anthropometric and demographic characteristics are found in Table 1.

Figure 1 Percentage contribution of flavonoid subclasses to total flavonoid intake

Figure 1
Percentage contribution of flavonoid subclasses to total flavonoid intake


Analysis of the 24h dietary recall calculated total flavonoid intake to be 510.2 ± 374.8mg/day, with a range of 5.9 – 1,524.2 mg/day. Black tea contributed 80% of total dietary intake and was the most notable dietary source of flavonoids. Other notable sources were green tea (7.5%), red wine (4.5%), with apples and oranges providing 1.7% and 1.6% respectively, when combined with their fruit juices. The dominant subclass of flavonoids was flavan-3-ols; these contributed 88% of total intake (Figure 1).

Total flavonoid intake was not significantly correlated with age, nutritional status or education. However, participants who displayed greater depressive symptoms (i.e. scored higher on the GDS) had a lower total flavonoid intake (r=-0.328 p=0.021).
Total flavonoid intake was significantly correlated with verbal fluency (r=0.319 p=0.025) (Table 2). Verbal fluency was also significantly correlated with the flavonoid subclasses flavonols (r=0.321 p=0.025), flavan-3-ols (r=0.323 p=0.023) and anthocyanins (r=0.298, p=0.038). No other significant associations were identified. A regression analysis was conducted to predict verbal fluency from total flavonoid intake, with age and education as covariates. Total flavonoid intake statistically significantly predicted verbal fluency score (β =0.319, p=0.025) controlling for age (β=0.042, p=0.765) and education (β=0.219, p=0.124). The overall model fit was r2=0.148.
After controlling for depression (GDS continuous score), bivariate correlations showed no significant relationship between total flavonoid intake or flavonoid subclasses was shown (Table 2).



The mean intake of total flavonoids (510mg/day) in this sample of older adults with mild to moderate Alzheimer’s type dementia is lower than the other estimations in older Australian adults, which were 683mg/day (5) (from 12 day food records) and 575mg/day (from a single 24h dietary recall) (39). However, the major dietary sources and percentage contributions from each flavonoid subclass are similar (5, 39). Black tea was the major dietary source of flavonoids (80%), and this finding highlights a limited fruit and vegetable consumption in this group.
The relationship between cognitive performance on the verbal fluency task (a measure of executive function), and flavonoid intake is supported by literature which suggests that executive function can be positively influenced by flavonoid supplementation and habitual flavonoid intake (40). The relationship between verbal fluency and intake of the flavonoid subclasses flavonols, flavan-3-ols and anthocyanins (but not flavanones, or flavones) may be related to the consumption of  black and green tea (the major sources of flavonols and flavan-3-ols) and berries (a major source of anthocyanins), in this group. The consumption of both green and black tea has been associated with improved cognition in older adults (41), although a recent systematic review considered the role of tea in mild-cognitive impairment and dementia progression and reported that the findings were too limited to draw conclusions (42).  Similarly, the consumption of anthocyanin rich strawberries and blueberries has been associated slower cognitive decline (43).
The lack of correlation between total flavonoid intake and education, nutritional status and age indicates that in this cohort these factors do not impact on total flavonoid consumption. This may be explained by tea consumption, the largest contributor to total flavonoid intake being a universally consumed item by all socioeconomic groups, and also reflects the lack of energy or micronutrients provided by this beverage, thus not impacting on nutritional status.
The positive association between depressive symptomatology (as measured by GDS) and flavonoid intake (r=-0.367, p=0.009) is interesting. The reduction in association between verbal fluency and flavonoid intake when depression was included as a covariate suggests that this relationship is confounded by the effect of depression on executive functioning. We speculate that epidemiological studies that have reported associations between flavonoid intake and cognitive outcomes, without controlling for depression, may have overestimated the strength of this relationship (7).
There is little consensus regarding which cognitive domain is impacted by flavonoid intake (40, 44) or which tool should be employed to measure this effect (44). We therefore used a battery of cognitive tests in order to investigate a wide range of domains of cognitive function, ensuring that each of the validated tests was sensitive and specific. Generalizability of the study findings is limited by the small sample size and the non representative nature of the convenience study sample. Other limitations include the inadequacy of using a single 24h dietary recall to estimate habitual dietary flavonoid intake. Aside from the limitations associated with this dietary assessment method, there are several well documented problems associated with utilising food composition databases to assign flavonoid content to selected foods to reflect dietary intake. These limitations include an incomplete list of flavonoid containing foods, non-regional specific data (there is no Australian database for the flavonoid content of foods comprising the Australian food supply), and the inability of a dietary assessment to account for the high intra-individual variation of flavonoid absorption and metabolism (45). These limitations may result large variations in estimations of flavonoid intake (6) that differ from the true value, and may hinder our interpretation of observational data that associates flavonoid intake with specific health outcomes.
In conclusion, dietary intake of flavonoids in a sample of older adults with Alzheimer’s disease was found to be somewhat lower than current Australian estimations for this age group, but the contributions of dietary sources are similar to the general older population. The identified association between cognitive functioning, depression and flavonoid intake in older adults with Alzheimer’s type dementia warrants further research in a larger sample to confirm the findings and to identify whether dietary interventions may be indicated.


Funding: This study was conducted with funding from the Illawarra Health and Medical Research Institute. The sponsors had no role in the design and conduct of the study; in the collection, analysis, and interpretation of data; in the preparation of the manuscript; or in the review or approval of the manuscript.

Acknowledgements: None

Conflict of interest: None

Ethical standards: This study was approved by the University of Wollongong and Illawarra Shoalhaven Local Health District Human Research Ethics Committee (HE11/175) and complied with current laws governing ethics in research.



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N. Cano-Cuenca1,2, J. Solís-García del Pozo1,3, J. Jordán1,4

1. Departamento de Ciencias Médicas. Facultad de Medicina de Albacete. Universidad de Castilla-La Mancha (UCLM). Spain; 2. Servicio de Farmacia. Hospital de Hellín. Spain; 3. Servicio de Medicina Interna. Hospital General de Villarrobledo. Spain; 4. Grupo de Neurofarmacología. Instituto de Investigación en Discapacidades Neurológicas-UCLM. Spain.

Corresponding Author: Joaquín Jordán, Grupo Neurofarmacología. Departamento de Ciencias Médicas. Facultad de Medicina de Albacete. Universidad de Castilla-La Mancha. Calle Almansa, 14. Albacete-02008. Spain. Telephone. +34-967599200. Fax+34-967599327. e-mail: joaquin.jordan@uclm.es



Background: Citicoline is considered an ingredient in particular foods in the USA and is available in pharmaceutical form in Europe and Japan. It has been postulated to render positive effects on the nervous system, either by increasing levels of neurotransmitters, or by affording neuroprotection. Methods: Several clinical trials have shown the efficacy and safety of this biomolecule in several neurodegenerative diseases and in acute ischemic stroke. Here, we have performed a systematic review to validate the effect of citicoline on MMSE, memory, attention, and basic activity of daily living. In electronic database searches, we found 14 randomized clinical trials reporting citicoline effects on cognitive function. Findings: A positive effect of citicoline on MMSE in acute ischemic stroke was found, which was not evidenced for Alzheimer disease or vascular dementia. On activities of daily living, citicoline failed to exert beneficial effects in patients with acute ischemic stroke or progressive cognitive impairment. Conclusions: Given the present data there is no evidence that supports advising patients with cognitive alterations to take chronic citicoline supplements. 

Key words: CDP-choline, cytidine, Alzheimer disease, dementia, cognition, meta-analysis, acute ischemic stroke. 



Besides being the central symptom of dementia, cognitive impairment is the principal cause of a wide range of disabilities affecting attention, mnesic, linguistic and visuo-spatial abilities (1). Alterations in cognitive functions are present in neurodegenerative diseases, including cerebrovascular disorders such a stroke or vascular dementia (2). Among the pharmacological arsenal tested in stroke is the biomolecule Citicoline (CDP-choline or cytidine-5´-diphosphocholine) (3). Although its mode of action is far from being clarified, evidence supports citicoline roles in cellular pathways related with neural cell death prevention. Thus, citicoline increases levels of neurotransmitters, including noradrenaline, dopamine and serotonin (4). Furthermore, citicoline might enhance tolerance to ischemic brain damage by preventing cell membrane damage and impaired phospholipid metabolism described during stroke (5). Preclinical evidence supports citicoline providing efficacy and optimal neuroprotective profile in stroke animal models (6, 7).

This neuroprotective role leaded the clinician to perform clinical trials aimed to ascertain the efficacy of citicoline on stroke [8-13] and other neurodegenerative diseases (8, 14, 15). However, the effect of citicoline on stroke is elusive (for literary reviews see (16-19), even more if take into account data from the latest clinical trials that failed to show beneficial results (20, 21). These neuroprotective effects lead other authors to suggest that citicoline might have beneficial impact on several cognitive domains (22), and several trials including patients of Alzheimer disease (10) or vascular dementia (23).

Meta-analysis combines findings from independent studies to assess the clinical effectiveness of healthcare interventions (22). Using this technique, the efficacy and safety of a drug (24, 25), or its lack of efficacy, such as in the case of the promising drug dimebon (26), can be determined. 

The lack of a systematic review that put together all the information on citicoline effects on cognitive function was the starting point of this work. Thus in this study, we performed a systematic review of the literature on citicoline and its efficacy on impairment associated to neurodegenerative diseases such as alterations in mini-mental state examination, memory, attention and finally the plausible effects on basic activities of daily living.


Material and Methods

We conducted a search for all clinical trials using citicoline to improve cognitive function, in patients affected by different pathologies causing neurological disorders. The studies were found by means of a MEDLINE and and in the Cochrane Central Register of Controlled Trials (CENTRAL) searches using the keywords “Citicoline” AND “cognitive» (July 2014). The bibliographic references of the selected articles were also examined to locate other possible publications not found in the above-mentioned search. The trials that were included meet the following criteria. 1. Double-blind placebo controlled with random assignment to citicoline or placebo. 2. Inclusion of patient with altered cognitive function. 3. Specification of medication doses and formulation. 4. Written in English. We have found 99 studies. Of these, 73 were rejected for different reasons (figure 1). Of the 26 remaining studies, 14 were included in our systematic review (Table I and Figure 1). The quality of each study was determined by using Jadad score that considers aspect related to biases such as randomization, blinding and reporting of loss to follow-up (27). This instrument gives a score from 0 (the worst score) to 5 (the best score). Two investigators (NC-C, JJ), independently extracted those publications identified here that describe controlled studies of citicoline in cognitive impairment. Disagreements were resolved in discussion with a third investigator (JSGdP).

We collected data on patients´ diagnosis, dosage used, duration of treatment and follow-up, inclusion and exclusion criteria and scales used for efficacy. Results were described for four domains: mini-mental state examination, memory, attention and basic activities of daily living.

– Mini-mental state examination (MMSE) (28). The MMSE is a common, validated screening instrument that is used as a general measure of cognitive function (lower score indicate greater impairment), includes questions about basic temporal and spatial orientation, attention, language, calculation, memory fixing and constructive praxis. 

– Memory: Different scales were used to assess memory. Briefly, Randt memory test for longitudinal assessment of mild and/or moderate memory deficits (29), memory subscale of Alzheimer’s Disease Assessment Scale (ADAS) (30) used to evaluate the severity of cognitive and noncognitive behavioral dysfunctions characteristic of persons with Alzheimer’s disease, California Verbal Learning Test popular clinical and research test that claims to measure key constructs in cognitive psychology such as repetition learning, serial position effects, semantic organization, intrusions, and proactive interference (31), Logical Memory consisting in  immediate repetition of short stories presented auditory (it is a subtest of Wechsler Memory Scale, a widely used clinical scale composing a number of subtest) (32) and the Rey Auditory Verbal Learning Test (RALVT) an easy to administer test that assesses many memory domains and is, therefore, widely used in the area of clinical neuropsychology (33).

– Attention: Two tests were used for determining the subject’s attention. The Toulouse-Pieron Test and the Trail Making Test are accessible neuropsychological instruments that provides the examiner with information on a wide range of cognitive skills (11).

– Basic activities of daily living (disability): two scales were used, basically for the evaluation of self-care and mobility. Barthel Index, a scoring technique that measures the patient’s performance in 10 activities of daily life (34) and the Index of Activities of Daily Living (ADL) a method of classifying heterogeneous groups of people with chronic illnesses, disabilities and impairments, and of describing their health needs and outcomes (35).

The statistical analyses were performed comparing citicoline with placebo in terms of efficacy wherever such comparison was possible. The efficacy measures were expressed as odds ratio or standardized mean diference with the relevant confidence interval (IC95%). We have used a random effect where heterogeneity among studies was found. A funnel plot, if possible, were used to evaluate potential selection bias in the studies. Chi2 of heterogeneity and I2 inconsistency statistic were used to measure heterogeneity regarding study results. In all tests, the level of statistical significance used was p<0.05. Analyses were performed using RevMan version 5. 



Our literature search revealed 14 clinical trials that were included in our study tested the efficacy of citicoline for improving cognitive functions in patients that were affected by altered cognition pathologies, such as vascular dementia, acute stroke, and Alzheimer disease.

Effects of citicoline on MMSE

Although we found four trials including 474 patients, of which 300 were treated with citicoline using the MMSE measure to evaluate cognitive function.

In two clinical trials, citicoline efficacy was tested in patients with vascular dementia, giving contradictory results. Chandra et al reported a marked improvement on the MMSE score compared with patients taking after two months (MMSE score: 23 in citicoline group and 14.4 in placebo group) and after 10 months (MMSE score: 23 in citicoline group and 12.2 placebo group) (12). On the other hand, Cohen et al. found no significant changes in MMSE scores at 6 and 12 months (23).  

In patients with acute ischemic stroke, Clark et al., evaluated the effect of three daily doses of citicoline (500, 1000 and 2000 mg) versus placebo (36). At 12 weeks, citicoline increased the percentage of patients with an optimal outcome in the MMSE (≥25). Remarkably, this effect appeared not dose dependent, since it was observed at 500 and 2000 mg but not 1000 mg (36). 

In Alzheimer disease patients, Alvarez et al. did not detect a difference in the MMSE score between placebo and citicoline (1000 mg, 12 weeks) (10).  


Table 1 Clinical trials included in this review


Citicoline effects on memory

In table II, we have summarized the eight clinical trials, including 1890 patients, which evaluated citicoline effects on memory function (9, 10, 13, 15, 23, 37, 38). 


Table 2 Clinical trials evaluating citicoline effects on memory

N.S. Non-significant. RAVLT, Rey Auditory Verbal Learning Test. 

Two trials used the Randt Memory Test to ascertain citicoline efficacy in patients with chronic cerebrovascular disease. First, Piccoli et al. revealed that citicoline induced a constant and progressive improvement (p<0.05) (37).  Second, in a subtest of this test, Capurso el al. found a significant difference in the memory index (p<0.05) (13). However, in patients with vascular dementia, citicoline failed to improve the California Verbal Learning Test (p=0.36) and Logical Memory (p=0.5) (23). Lack of citicoline-induced positive effects were also reported by Alvarez-Sabin et al. Using the Auditory Verbal Learning Test, these authors did not detect differences in patients with post-stroke vascular cognitive impairment at 6 and 12 weeks (p=0.807 y p=0.873) (39).

In the citicoline brain injury treatment trial(COBRIT), citicoline failed to afford any improvement in the California Verbal learning Test score in patients with traumatic brain injury (38). In patients with bipolar disorder with cocaine dependence, Brown et al. reported that citicoline leads to an enhancement in the RAVLT alternative Word list (p=0.006) but not in RAVLT total Word (p=0.439) or RAVLT delayed recall (p=0.105) (15). In addition, two more trials described a positive but not statistically significant tendency to improve memory in volunteering patients with relatively inefficient memory (9) or Alzheimer disease  (10). 

Effects of citicoline on attention

We identified five trials analyzing citicoline effects on attention, enclosing a total of 1.721 patients (23, 37-40). In patients with chronic cerebrovascular disease, citicoline induced a significant decrease in the number of incorrect responses in the Toulouse-Pieron test (p<0.05) (37). Similarly, Alvarez-Sabin, at 6 (p=0.019) and 12 (p=0.014) months of treatment, evidenced less deterioration of post-stroke vascular cognitive impairment in attention-execution (Stroop Color Word Interference test, Trails A and B and Symbol digits Modalities Test, Mental control, Digit Span) (39). 

However, using the Trail Making Test scores, we did not find citicoline-induced improvements in patients affected by Alzheimer disease (p=0.74) (40), vascular dementia (p=0.58) (23) or traumatic brain injury (38).


Figure 1 Flow chart outlining the search strategy and results of the different steps



Figure 2 Forest plots showing individual and pooled odd ratio (95%) for the associations between citicoline (2000 mg and 500 mg) and Barthel index (≥95)


Effects of citicoline on basic activities of daily living

 The effect of citicoline on the patient ability to perform activities of daily living was evaluated in 5 clinical trials that included 4137 patients, 2334 of which were treated with citicoline. 

In acute ischemic stroke patients, Clark et al. evaluated citicoline efficacy in three clinical trials, leading to heterogeneous results. Interestingly, in the first trial, with citicoline administered at 500, 1000, and 2000 mg, only at a daily dose of 500 mg citicoline resulted in a Barthel-index improvement (p=0.03) (36). Their second trial was addressed to compare citicoline (500mg) versus placebo (41), but this did not yield positive results. In the third trial, the authors compared a daily dose of 2000mg citicoline versus placebo. Although initially (at 6 weeks) a higher proportion of patients in the citicoline group showed a score higher or equal to 95(placebo 21%, citicoline 27%; p=0.04), this difference was lost at 12 weeks (42). In addition, in a different trial, Davalos et al. did not find citicoline effects in this kind of patients  (20). Our meta-analysis of these data shows that citicoline did not significantly alter the Barthel index at the doses of either 500mg (OR 1.43; IC 95% 0.64-3.19)or 2000mg(OR 1.13; IC 95% 0.86-1.49) (Figure 2). 

Using the ADL scale in elderly patients with progressive cognitive impairment, Putignano et al., did not find effectiveness for citicoline, although, they denoted a trend towards favorable scores in the functional independence (43) 



Prompted by the fact that citicoline has been shown to be a useful treatment for neurodegenerative and cerebrovascular diseases, we have evaluated its ability to improve cognitive function by performing a systematic review. To do so, we focused on scales that measure aspects such as MMSE, memory, attention, and basic activity of daily living.  

Our data reveal a positive effect of citicoline on MMSE in acute ischemic stroke, which was not evidenced for other diseases where cognitive function is compromised, including Alzheimer disease or vascular dementia. However, this positive improvement was found in a single study,and only at a daily dose of 500 and 2000 mg but not 1000 mg. So, it will be interesting to corroborate these data in a new clinical trial. In addition, in vascular dementia, our study revealed contradictory results, which makes it difficult to draw solid conclusions. Furthermore, we found lack of evidence for citicoline effects on cognitive impairment associated to Alzheimer disease. This conclusion seems contradictory to the previous conclusion reached by Secades in a nice and elegant, but not systematic, review (17). 

In addition, eight studies reporting citicoline effects on memory were found. In chronic cerebrovascular disease patients, two studies yielded favorable results. However, other studies failed to show a positive effect on post-stroke vascular cognitive impairment, AD, or aging. Unfortunately, we were unable to perform a meta-analysis as the authors used different scales with different scores and thresholds to measure sensibility. These disparities constitute a handicap to find plausible positive effects.

We have also analyzed the effects of citicoline on attention. Positive results were observed in two studies performed with post-stroke patients and chronic cerebrovascular disease. However, citicoline failed to produce this positive result when the patient suffered from Alzheimer disease, traumatic brain injury, or vascular dementia.

Our last goal was focused on the effects of citicoline on the activities of daily living. Our meta-analysis, which included four trials, revealed that citicoline failed to exert beneficial effects in patients with acute ischemic stroke (Barthel index) or progressive cognitive impairment (ADL score). 

Why citicoline improves some cognitive impairments but fails to do so with others remains unknown (43, 44, 45) Pre-clinical evidence supports citicoline efficacy and an optimal neuroprotective profile in stroke animal models (7). In a recent review, Overgaard concluded that citicoline is the only drug that, in different clinical stroke trials, continuously showed neuroprotective effects (3).

However, we cannot ignore that often important causes of irreproducibility of experimental results in clinical settings are the use of large drug doses in most animal experiments (18) or the lack of methodological rigor, and these lead to an inflated treatment effect (46) Considering that citicoline is an essential intermediate in the synthesis of structural phospholipids of cell membranes and its formation from phosphorylcholine is the rate-limiting step of this biosynthetic pathway, one could hypothesize that it needs to have a strict control. In fact, citicoline is hydrolysed into choline and cytidine to be resynthesized later in the brain (47). In this scenario, long treatment periods would result in a negative feedback and result in readjustment of the available citicoline levels, yielding a non-efficient drug. Supporting this idea, Baab et al. found that phospholipid synthesis and turnover were stimulated at 6 but not 12 weeks of oral citicoline treatment. Moreover, these authors correlated results from the California Verbal learning test with an increase in phophodiesters (48). Then, only under acute damage (e.g. acute stroke), where this homeostatic response does not efficiently regulate endogenous values, citicoline administration results in an efficient protection. On the other hand, in acute events citicoline might result in an inhibition of cell death pathways. For instance, in an experimental model, citicoline markedly lowered brain edema and blood-brain barrier permeability, enhanced the activities of superoxide dismutase, increased glutathione levels, and reduced the levels of malondialdehyde and lactic acid  (49). Other mechanisms suggested to be involved include prevention of phospholipase A2 activation  (50), which is involved in transient cerebral ischemia (51). 

There is a Cochrane’s Systematic review about this topic performed by Fioravanti M and Yanagi M, that yielded different results  (52). The authors concluded that there was some evidence that CDP-choline has a positive effect on memory and behaviour. The effect on attention measures was not significant (p=0.22). Nonetheless, the characteristics of this review are different from ours since the outcome analyzed differ. For instance, the effect of citicoline on the MMSE and on activities of daily living is novel in our review. We have to acknowledge that our study presents limitations related to the difficult process of selecting trials using citicoline.  In addition, our systematic review shows the heterogeneity of trials using citicoline. This heterogeneity is present in parameters such as treatment duration, the number of patients, the follow-up period, and the scores used. Moreover, we were negatively surprised by the way the authors of the trials had reported their results. Whereas some authors gave mean scores, others categorized them when they referred to the same scale. Indeed, we found that 5 reached a Jadad score of zero (8, 14, 21, 53, 54), which is indicative of a lack of answer to relevant key questions such as «Was the study described as randomized, or as double blind?», «Was there a description of withdrawals and dropouts?»Due to these discrepancies, it is difficult to make a thorough analysis of the data and might easily lead to wrong interpretations. 

Finally, although our study was not undertaken to determine citicoline safety, we validate the general idea that citicoline presents a good safety profile. Ten of the trials included in our study described adverse events. Enclosing 2254 patients in total, 1400 were treated with citicoline. The side effects most frequently reported were effects on the central nervous system in both the citicoline (127 events, 10%) and the placebo (103 events, 13%) groups. However, we did not find significant differences between these groups.

In summary, our data suggests that citicoline may improve MMSE in acute stroke patients. However, to reach a solid conclusion for this and other chronic diseases such as Alzheimer disease and vascular dementia, we need to reach an agreement on the test scales and how to report the scores before performing more trials. Awaiting the completion of new clinical trials including higher numbers of patients in order to obtain more consistent results, we would not advise the use of citicoline as effective treatment in patients with cognitive impairment.


Ethical Standards: None disclosed.

Conflicts of Interest: The authors declare that they have not conflicts of interest.



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L. Buchanan1, K.E Charlton2, S. Roodenrys3, D. Cocuz3, T. Pendergast3, G. Ma4


1. School of Health and Society, Faculty of Social Sciences, University of Wollongong, NSW, Australia; 2. School of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, NSW, Australia; 3. School of Psychology, Faculty of Social Sciences, University of Wollongong, NSW, Australia; 4; Institute of Clinical Pathology and Medical Research (ICPMR), Westmead Hospital, Sydney, NSW, Australia.

Corresponding Author: Karen E. Charlton, School of Medicine, Faculty of Science. Medicine and Health, University of Wollongong, Wollongong, NSW 2522, Tel: +61 2 4221 4754; Fax: +61 2 4221 3486; Email: karenc@uow.edu.au


Objective: This study aims to investigate whether iodine status is associated with cognitive functioning and mood state in a sample of healthy older Australians. Design: Cross-sectional study. Setting: Illawarra region of New South Wales, Australia. Participants: Eighty-four men and women (25 males; 59 females) aged 60-95 years with normal cognitive function. Measurements: Three repeated fasting urine samples were collected a week apart to assess median urinary iodine concentration for the group. Usual dietary iodine intake was measured using an iodine-specific food frequency questionnaire and three repeated 24-hour dietary recalls while nutritional status was assessed using the Mini Nutritional Assessment (MNA). Cognitive function was assessed by the CogState battery of tests and the Rey Auditory Verbal Learning Task (RAVLT) and mood state determined by the Geriatric Depression Scale (GDS). Associations between iodine status and cognitive tests were assessed by Wilcoxon signed-rank, Pearson, and Spearman rank correlation tests. Results: Median urinary iodine concentration (MUIC) indicated mild iodine deficiency (71μg/L; IQR = 55 – 102 μg/L). Iodine status was not significantly associated with any domains of cognitive function. Memory was negatively correlated with mood state (r = -0.375; P<0.05) and positively associated with nutritional status (r = 0.235; P<0.05). Conclusion: Iodine status is not associated with cognitive functioning in a sample of older people with mild iodine deficiency. It remains to be seen whether correction of more severe iodine deficiency in this age group would have a beneficial impact on domains of attention, visuospatial processing, and executive processing.

Key words: Iodine, dietary intake, cognition, mood state, older adults.



Iodine plays a key role in maintaining the normal function of the thyroid, and is an essential component in the molecular structure of thyroid hormones, thyroxine (T4) and triiodothyronine (T3) (1). Deficiency in thyroid hormone production leads to a generalised reduction of regional cerebral blood flow and brain activity, which in turn may adversely affect cognitive functioning (2). Various studies have demonstrated poor thyroid functioning to be associated with depressive symptoms, as well as cognitive decline in adults (3-6). Despite numerous studies showing associations between iodine repletion and improved cognitive performance in young children (2, 7-9), evidence of this type is not available for older people. There is some evidence that malnutrition impairs cognitive abilities in older persons (10-13) but this is not related to a suboptimal iodine status, specifically. Given that impaired cognitive abilities and mood state disorders are important determinants of independence in older adults (3), further elucidation of dietary factors that may be targeted for intervention is of particular importance.

Iodine deficiency re-emerged among Australian school-aged children and pregnant women in the 2000s (14-19). In an attempt to address this issue, mandatory fortification of iodised salt in bread was introduced by Food Standards Australia and New Zealand (FSANZ) in October 2009 (20). Evaluation of the impact of this public health strategy has focused on pregnant women and schoolchildren (21-24), but the most recent national health survey data on nutritional biomarkers suggests that the mild iodine deficiency has been corrected in older adults.

Over 14% of the Australian population is aged 60 years and older (25). A decline in cognitive functioning with age seems inevitable. Although it is difficult to clearly distinguish pathological effects of aging on cognitive function from non-pathological, it is clear that many factors may contribute to cognitive decline, including dietary factors. It is also clear that cognitive decline has a major impact on everyday functioning and is a major cause of older adults entering care (26). Given the evidence described above and the finding that treatment of hypothyroidism has been shown to improve cognitive function (27), it is possible that dietary iodine may be associated with the current level of cognitive function in older adults. The aim of this study was to assess the association between iodine status and domains of cognitive function, mood and memory in a sample of older Australians prior to introduction of a mandatory iodine fortification programme.



One hundred and ten English-speaking men and women aged 60 – 95 years living in aged care facilities (independent retirement villages, assisted living, and low care facilities) in the Illawarra region of New South Wales, volunteered to participate in the study. Twenty-six people were excluded because of one or more of the following exclusion criteria: a) diagnosed dementia and/or Alzheimer’s disease, b) cognitive decline as indicated by a Mini-Mental State Examination (MMSE) score of <=23 (28), c) a previous stroke, d) current use of thyroxine or any other medications that may affect memory, 5) uncontrolled hypertension (blood pressure (BP) ≥ 160/95 mm Hg), or e) uncontrolled diabetes (blood glucose (BG) ≥ 7.8 mmol/l).


Assessment of Iodine Status and Nutritional Status

Participants were visited in their homes weekly over a three week period for collection of spot urine samples, and to administer the dietary assessments and cognitive performance tests. First voided urine samples were collected and stored at -80°C until all samples could be batch-analysed by the accredited laboratory of the Institute of Clinical Pathology and Medical Research (ICPMR), Westmead Hospital (Sydney, NSW, Australia). Urinary iodine concentration (UIC) was analysed using an adaptation of the Sandell-Kolthoff method using the microplate method (29) with ammonium persulphate digestion and microplate reading. Sensitivity of the urinary iodine assay is 5 µg/L. At 46 µg/L (± 7.72 (i.e. 2SD)) the coefficient of variation (CV) is 16.7%, at 153 (± 8.9) µg/L the CV is 5.8%, while at 347 (± 30) the CV is 8.65%

Dietary iodine intake was measured by a validated iodine-specific Food Frequency Questionnaire (FFQ) (30) and three repeated 24-hr dietary recalls (3 x 24hr DR). Nutritional status of subjects was assessed using the validated 18-item Mini Nutritional Assessment (MNA) and scored according to the categories of ≥ 24, 17 – 23.9, and <17, for classification of well nourished, at-risk of malnutrition, or malnutrition, respectively (31).

Cognition, Memory and Mood State Assessments

Tasks from the CogState battery of tests (32) were presented on a laptop computer and tests were delivered in the format of a set of digital playing cards. This method has been shown to be readily understandable and accepted by older participants (33). Participants were given 45-50 mins to complete the tests which examined their domains of attention, visuospatial processing, and executive processing, as listed in Table 1.

Table 1 Task information of the Cogstate battery of tests and cognitive function assessed

* Description of variable codes listed in Table 2. (CogState Ltd., 2009a)

Memory was assessed using the Rey Auditory Verbal Learning Task (RAVLT) (34), which requires participants to remember a list of semantically unrelated words (see Table 2 for details of the measures from this task). The 15-item Geriatric Depression Scale (GDS) (35) was administered to assess participant’s mood state (score = 0 – 15). A higher score indicates greater levels of depressive symptomatology and a cut-off of 5 indicates some form of depression (35-36).

Table 2 Cognitive measures in the CogState battery of tests

(CogState Ltd., 2009b)


Data analyses

The mean of the three urinary iodine concentrations (UIC) of each participant was used to assess group median UIC, according to the UIC reference values of the World Health Organization and the International Committee on the Control of Iodine Deficiency Disorders (ICCIDD) [iodine-replete: UIC ≥ 100 µg/L; iodine-deplete: UIC ≤ 100 µg/L] (WHO/UNICEF/ICCIDD 1994). UIC was also expressed as a ratio of UIC:creatinine (µg/g) (37).

Statistical analysis

Statistical analyses were performed using the Statistical Package for Social Sciences (V15.0.0 SPSS Inc., Chicago IL, USA) (38). Tests for normality of the data were performed using the Kolmogorov-Smirnov test. Pearson or Spearman rank correlation coefficients were used to determine the relationship of the methods to measure iodine status, and the association between iodine status, cognitive and memory functioning, and mood state. Statistical significance was set at p < 0.05.


The characteristics of the 84 participants (25 men; 59 women) are shown in Table 3. Median UIC indicated mild iodine deficiency (71μg/L; IQR = 55 – 102 μg/L). When calculated as a ratio of UIC: creatinine, the mean value for 3-day spot urine samples was 123.9 ± 55.3 µg/g. Dietary iodine intake of participants in this study, measured by both the iodine-specific FFQ and the average of the three 24-hr dietary recalls were higher than those reported in the 22nd Australian Total Diet Study; median dietary iodine intake for men was 106 ug/day (FFQ) and 117 ug/day (24-hr dietary recall) while for women was 107 ug/day (FFQ) and 105 ug/day (24-hr dietary recall). Details of participants’ dietary intake are reported elsewhere (Tan et al. 2013). All except four subjects (5%) were classified as being well nourished, according to the MNA classification.

Table 3 Tests information of the Rey Auditory-Verbal Learning Test (RAVLT) and the cognitive function assessed

(Senior, 2000)

Association between Iodine status, cognitive function, mood state and memory

Only four variables in the CogState battery of tests were significantly associated with either urinary iodine status or dietary iodine intake, but some were unexpectedly inversely correlated. These included: accuracy of performance in the Set Shifting Task (SETacc) and UIC (r= -0.253; p<0.05); the number of errors made in the Groton Maze Learning Task (GML) ((r = 0.343; p<0.05) and dietary iodine intake (FFQ); speed of performance in the Detection Task and dietary iodine intake (3 x 24-hr DR) (r = -0.231; p<0.05); and the accuracy of performance in the Set Shifting Task and dietary iodine intake (3 x 24-hr DR) (r = -0.261; p<0.05). Analyses were also performed using iodine expressed per unit creatinine and iodine/creatinine/body weight to account for renal function and body weight of the subjects. However, findings did not change (data not shown). None of the tests in the RAVLT series were significantly correlated with UIC. The RAVLT False Alarm (FA – i.e. number of words indicated during a recognition task as being on the list which, in fact, were not) was inversely associated (r= -0.238; p< 0.05) with reported dietary iodine intake (FFQ).

Mood state was not related to either UIC nor dietary iodine intake .

Association between Nutritional status and Cognitive and Memory Functions

A higher MNA score (i.e. better nutritional status) was inversely associated (r =-0.258, p<0.05) with number of errors made by the subjects in the GML task, but no association with the other tasks were found. MNA score was significantly correlated with performance in three measures in the RAVLT task, namely Ravlt (I-V) (r=0.235, p<0.05) which measures performance across the 5 learning trials; Ravlt Int (r=0.349, p<0.05) which measures performance in learning a new list of words; and Ravlt FA (r=-0.246, p<0.05). After removing an outlier on the GDS measure, MNA did not correlate significantly with GDS score.

Association between Mood state and Cognitive and Memory Functions

One participant was classified as mildly depressed, while the rest scored normally on the Geriatric Depression scale (Yesavage et al., 1983). None of the tasks within the CogState battery of tests were associated with the depression score. GDS was significantly inversely correlated with the tests within the RAVLT (r = -0.226 to -0.375) except for Ravlt Miss and Ravlt FA. The lower the GDS score (less depressed), the better the subjects performed in the RAVLT (RAVLT I-V r= -0.375; RAVLT Int r= -1.239; RAVLT VI r= -.0.380; RAVLT Hit r=-0.226).

Table 4 Demographic and clinical characteristics of study subjects (n = 84)

a. Mean ± standard deviation; b. Calculated as kg/m2



Contrary to our study hypothesis, we found no evidence that higher iodine levels, assessed using repeated urinary or dietary measures, were associated with better cognitive function, memory performance or mood state in a sample of healthy, independently-living older people. Similarly, performance on tests across a range of cognitive domains was not associated with a composite and validated measure of nutritional status. However, nutritional status and level of depression appear to be independently related to memory function, as indexed by performance on the various measures of the RAVLT task.

This sample of otherwise healthy older Australians had mild iodine deficiency (median UIC = 71μg/L), as had been reported in groups of children and pregnant women in the country (14-16, 37-38) prior to introduction of the mandatory iodine fortification program in Australia in 2009 (20). A lack of published literature on the impact of suboptimal iodine intakes on cognitive function and mood state in older people with no clinical cognitive impairment limits interpretation of our findings. A randomized, controlled trial (41) which investigated the effects of iodized poppy seed oil on cognitive and motor function in school-aged children with normal thyroid function reported no benefits after four months of intervention, and suggested that low urinary iodine biomarkers, in the presence of normal thyroid function does not affect cognitive function.

Table 5 Pearson correlations of the tasks within the CogState battery of tests with urinary iodine concentration and dietary iodine intakes from the iodine-specific food frequency questionnaire (ISFFQ) and the 24-hr dietary recall (24-hr DR)

DET= Detection Task; GML=Groton Maze Learning Task; OCL=One Card Learning Task; ONB= One Back Task; TWOB= Two Back Tasks; SET= Set Shifting Task; ter (1,2…)= Total number of errors in GML (round 1,2…); lmn= Speed of performance; lsd= Consistency of performance; acc= Accuracy of performance; * Correlation is significant at the 0.05 level (2-tailed).

Several possibilities may explain the lack of association between iodine status and cognitive functioning among elderly people. Iodine-related cognitive deficits may only occur in individuals with hypothyroidism, a group that we attempted to exclude from the present study. Hashimoto et al. (42) found that congenital hypothyroidism caused cognitive and memory dysfunction in mice. Experimental hypothyroidism in their study resulted in impaired learning in developing mice. Similarly, another study on iodine-deficient or hypothyroid rats suggested that iodine deficiency and hypothyroidism during critical periods of brain development resulted in abnormalities in the hippocampus, an area of the brain which is known to be important for cognitive and memory performance (43). An intervention trial conducted by Zimmermann et al. (2) demonstrated that iodine treatment for 24 weeks improved iodine status and cognition of children with moderate iodine deficiency. Since cognitive deficits may only occur in iodine-deficient individuals with hypothyroidism, the assessment of thyroid hormones may have provided more insight into the iodine-cognition relationship.

Another explanation may be that iodine deficiency may affect fetal brain development but not impact on functioning in an adult’s brain. Indeed, experimental studies in the rat model have shown that maternal (46) and fetal iodine deficiency (45) results in early developmental defects in the hippocampus of the brain. The crucial role of thyroid hormones on human fetal brain development is well established (46-47). However, there are limited studies on the impact of iodine deficiency on cognitive functioning of adults. One study that investigated the effect of thyroid hormone replacement on cognitive function in adult hypothyroid rats (48) did not demonstrate cognitive benefits after the thyroid hormone treatment, although one small study with humans did find some benefit (27).

Table 6 Pearson correlations of the tests within the RAVLT (Rey Verbal Learning Task) with urinary iodine concentration and dietary iodine intakes from the iodine-specific Food Frequency Questionnaire and the 24-hr Dietary Recall

*Correlation is significant at the 0.05 level (2-tailed).

The negative correlation between iodine measures and performance on some cognitive task measures is unexpected. The speed of performance in the detection task was faster for participants with higher levels of iodine, as might be expected if iodine is important for cognitive function. However, participants with high iodine consumption made more errors on some tasks. This correlation may be explained by a speed-accuracy tradeoff in those tasks, where speed and accuracy were negatively correlated. Those participants with higher iodine intake had a tendency to respond more quickly but less accurately. This may be an effect of iodine on the overall pattern of responding or it may be coincidental and reflect a type I error, given the large number of correlations that were tested.

Memory (verbal learning and recall) and performance on the other cognitive tasks was not associated with the iodine status of our participants. Similarly, a clinical trial by Chandra (55) found that supplementation with vitamins and trace elements did not significantly improve memory in healthy elderly subjects. Supplementation studies that have found significant improvements in memory with multivitamin supplementation included frail elderly participants or those who had already experienced memory difficulties (53, 56). Memory deficits associated with thyroid function may only be apparent in individuals with severe iodine deficiency or altered thyroid function.

Table 7 Spearman correlations of the tests within the Rey Auditory Verbal Learning Task (RAVLT) with the 15-items Geriatric Depression Scale (GDS)

Ravlt (I-V)= Sum of learning trials I through V, involve the repeated reading of the test list (List A); Ravlt I= Trial 1, measure of immediate memory; Ravlt Int= Interference trial in which a new list (List B) is read to the subject; Ravlt VI= Trial 6, subject is asked to recall as many words as he/she can from the List A after the interference trial; Ravlt Hit (Hits)= number of words from List A recognised; Ravlt Miss (Misses)= number of words on List A that were not recognised; Ravlt FA (False Alarms)= number of words indicated as being on the List A that were, in fact, not; ** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed).

Memory performance was however associated with nutritional status and mood state. Our findings are consistent with other studies. Feng et al. (57) reported a positive association between better performance on the RAVLT test and a higher Vitamin B-12 intake. Similarly, The NEMO Study Group (58) demonstrated that micronutrient supplementation, though not inclusive of iodine, improved verbal learning and memory in Australian school-aged children. Several cross-sectional studies suggest an association between vitamin B-12 and iron intakes and memory in children (59-60). An inverse association between mood state and memory function in healthy populations has been well documented (61).

Limitations to the study include potential bias in the measurement of cognition. The CogState battery of tests has been shown to have high reliability and sensitivity when used to assess cognitive performance of older people, however many of these validation studies have involved older adults with some form of cognitive impairment, for instance, those at risk of having dementia or those with HIV- associated neurocognitive impairment (49-50). Clinical trials that used a computerized battery of cognitive tests have failed to identify any significant effect of multivitamin supplementation on cognitive performance among healthy elderly (51-53). It may be that the types of tests included in this format are not sufficiently sensitive to assess subtle differences among healthy older individuals. Older adults with low MMSE scores were not eligible for inclusion in the study, which may have resulted in a range and distribution of cognitive function test results that is too narrow to detect significant relationships with iodine status.

The internationally recommended method for assessing population-level adequacy of iodine status was used in the current study, namely median urinary iodine concentrations (MUIC), expressed as µg per litre of urine. Reference values for MUIC have been developed for schoolchildren aged 6 – 12 y, in whom an average urinary excretion volume of 1 litre per day is assumed (62). Age-related impairments in renal function may affect urinary volume output in older people and thereby limit interpretation of the MUIC values. Using laboratory reference cut-offs for urinary creatinine, and assuming a urinary volume of 1.5 L per day, 44% of the study subjects had values below the lower range (data not shown). It is therefore possible that spot UIC values may be under-estimating 24 hr excretion in this study population, as has been reported by Kim et al. (37). A review has identified that UIC is a useful biomarker of iodine status, and that an association between UIC and iodine supplemental intake exists. The review goes on to demonstrate that bioavailability of dietary iodine intake is high (63).

A strength of the current study is that it attempted to capture day-to-day variability of iodine consumption by the collection of three repeated spot urine samples for measurement of UIC, rather than relying on a single collection. This was an attempt to overcome the unacceptably large intra-individual variation associated with a single spot urine sample that may not provide a true picture of habitual iodine intake and underestimate low intakes in a deficient population (64). We have previously reported an association (r = 0.230;P < 0.05) between urinary iodine concentrations and three repeated 24-hour dietary recalls (30), which indicates that UIC provides a valid indication of dietary iodine intake.

Other limitations include the cross-sectional study design which provides a snapshot of both cognitive function and iodine status of individuals at only one timepoint. The cross sectional analysis allows for hypothesis generation, but prospective studies are needed to identify a causal effect between long-term exposure to sub-optimal iodine intakes and subsequent cognitive dysfunction in old age. The study population is not representative of the general geriatric population as the convenience sample was recruited from one geographical are of regional New South Wales, Australia. Generalizability of the findings is thus limited.

The lack of an association between iodine status and cognitive function needs to be interpreted against the context of a relatively healthy, well educated population with mild iodine deficiency. Participants in the present study were all highly motivated volunteers, who were either independently living at home or were in low-level care residential facilities, and had a surprisingly good nutritional status. Different associations may be evident in populations with moderate and/or severe iodine deficiency and in those with altered thyroid function, as in those with evidence of malnutrition. In addition, thyroid hormone assessment, which is sensitive and specific, may provide a better indication of iodine status than urinary and dietary iodine values.



Iodine status was neither associated with cognitive performance nor mood state in a sample of healthy older Australians. Memory function was positively associated with nutritional status while negatively influenced by depressed mood. Future studies may include older participants with severe iodine deficiency or with hypothyroidism to further examine a possible relationship between iodine intake and cognitive function in older adults.

Ethical Standards: The study protocol was approved by the University of Wollongong Human Research Ethics Committee and all subjects provided written informed consent.

Conflicts of Interest: No authors have any conflicts of interest to declare


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