Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-18T17:06:14.293Z Has data issue: false hasContentIssue false

Association between dietary saccharide intake and self-reported memory performance in middle-aged adults

Published online by Cambridge University Press:  09 May 2008

Talitha Best*
Affiliation:
School of Psychology, Flinders University, GPO Box 2100, Adelaide, South Australia5001, Australia
Eva Kemps
Affiliation:
School of Psychology, Flinders University, GPO Box 2100, Adelaide, South Australia5001, Australia
Janet Bryan
Affiliation:
School of Psychology, University of South Australia, Adelaide, Australia
*
*Corresponding author: Dr Talitha Best, fax +61 8 8201 3877, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

The aims of the present study were to assess dietary intake of saccharides in middle-aged adults, and to determine whether intakes of these sugar nutrients were related to self-reported memory performance. A population-based sample of 1183 men and women (aged 40–60 years) completed questionnaires assessing everyday memory function. Dietary intake status of saccharides was estimated using a self-completed, quantified FFQ. After controlling for demographic and health measures (for example, time spent exercising, smoking and alcohol consumption), saccharide intake was related to better self-reported memory functioning. Thus, longer-term intakes of saccharides through the usual diet may be positively related to perceived memory performance in mid-life.

Type
Full Papers
Copyright
Copyright © The Authors 2008

The impact of nutrition on aspects of health and psychological state, including cognition, is gaining increasing scientific interest(Reference Dye, Lluch and Blundell1). A growing body of literature has shown positive effects of specific nutrients, including folate, vitamins B6 and B12, thiamin, niacin, Zn, Fe, antioxidants, fatty acids and amino acids on cognitive performance(Reference Bryan2Reference Morris, Evans, Bienias, Scherr, Tangney, Hebert, Bennett, Wilson and Aggarwal4), indicating that nutrition can influence brain functioning and cognition. More recently, emerging research suggests potential benefits of saccharides to cognition(Reference Best, Kemps and Bryan5).

Saccharides are biological sugars that are essential for the healthy functioning of the body and brain(Reference Dwek6Reference Bertozzi and Kiessling8). They are found in plants, primarily fruit and vegetables, such as radishes, leeks, mushrooms, asparagus, apples and pears(Reference Ramberg and McAnalley9). In the brain, saccharides are involved in the proper functioning of synapses and neurotransmitters and therefore the electrical activity of neurons(Reference Kleene and Schachner10, Reference Martin11) as well as the integrity of the central nervous system in general(Reference Bandtlow and Zimmermann12). Hence, because of this wide-ranging role of saccharides in brain function, saccharides are likely to affect a broad array of cognitive abilities. Of the over 200 known saccharides, glucose has been the most widely researched. Although glucose is not invariably linked to enhanced cognition, several studies have demonstrated positive effects of this monosaccharide on cognitive performance, with stronger effects found for performance on tasks of memory compared with other cognitive functions(Reference Benton, Owens and Parker13Reference Sunram-Lea, Foster, Durlach and Perez18).

Accumulating evidence from supplementation studies in animals and human subjects suggests that other saccharides, in particular the polysaccharides fucose, mannose, galactose, rhamnose, arabinose and xylose, may also be linked to improved cognition. In particular, administration of fucose for several days has been shown to enhance hippocampal function and improve memory performance in chicks and rats(Reference Matthies, Staak and Krug19Reference Rose21). Additionally, injections of fucose, mannose and galactose to the brain over a period of 30 d have been found to improve spatial learning in rats(Reference Fong, Neff and Hadjiconstantinou22).

In human subjects, the research is limited. Single case reports provide further evidence for positive effects of saccharides on cognition. For example, fucose supplementation over 9 months administered by gastrointestinal tube improved speech and language abilities of a young child with leucocyte adhesion deficiency type II(Reference Marquardt, Luehn, Srikrishna, Freeze, Harms and Vestweber23). In addition, supplementation with a combination of saccharides, including fucose, galactose, mannose, arabinose and xylose, over 4 weeks improved the cognitive abilities, including retrieval from short-term memory, of an 8-year-old boy with dyslexia(Reference Benton24). Furthermore, a 5-week supplementation of these saccharides in clinically diagnosed alcoholics showed a trend towards improvement in self-reported cognition(Reference Dykman and Briggs25). Further, single-dose oral ingestions of the same combination of saccharides increased brain activity, as measured by electroencephalograph, and was associated with a trend towards improved performance on tasks of attention in a non-clinical sample of young adults(Reference Wang, Pivik and Dykman26, Reference Wang, Szabo and Dykman27). Finally, a single-dose oral ingestion of a combination of saccharides produced better scores on tasks of memory than a placebo in healthy middle-aged adults, although this difference was not statistically significant(Reference Best, Bryan and Burns28).

The absence of statistically significant short-term effects of the aforementioned polysaccharides on cognitive performance may be because of their role in the brain. Specifically, unlike glucose, these saccharides are thought to play a long-term structural and functional role in the brain, such as the development and function of neuronal membranes and synaptic junctions(Reference Best, Kemps and Bryan5). As a result, any saccharide effects on cognition are likely to be subtle and may only become apparent following intake over longer periods of time. In support, a recent longitudinal study(Reference Morris, Evans, Tangney, Bienias and Wilson29) found that over a 6-year period, consumption of vegetables such as zucchini, eggplant, broccoli and lettuce, which are thought to be rich sources of saccharides, was associated with slower rates of cognitive decline in older adults. Assessment of usual saccharide intake in the diet presents a non-invasive procedure for examining potential longer-term effects of saccharide intake. Indeed, a recent investigation of dietary saccharide intake and cognitive performance in middle-aged adults found that a higher intake of saccharides was related to better verbal memory performance(Reference Best, Kemps and Bryan30). However, the study was limited by the nature of the assessment of saccharide intake, which was estimated from the number of servings of certain vegetables and fruit believed to be rich in saccharides.

Thus, the present study aimed to determine intake of saccharides more accurately using detailed assessment of dietary saccharide intake in a large, population-based sample of middle-aged adults and examined whether intake was related to self-reports of memory performance. To our knowledge, the present study is the first to provide a comprehensive estimate of saccharide intake in adults. Middle-aged individuals were chosen because the first signs of age-associated cognitive decline often become apparent in mid-life(Reference McDaniel, Maier and Einstein31, Reference Nicolas, Nourhashemi, Lanzmann-Petithory and Vellas32).

Methods

Participants

Participants were recruited through a letter of invitation sent to 2000 women and 2000 men randomly selected from the 40–60-year-old age band of the South Australian electoral rolls. As voting is compulsory in Australia, this random selection of potential participants is likely to closely approximate a random sample of the population. A total of 983 (23·66 %) volunteers expressed interest in participating and were sent two questionnaires to complete. Of these, 498 women and 333 men returned completed questionnaires, yielding a response rate of 84·54 % of those who volunteered. Further recruitment through media publicity resulted in another 478 volunteers, of whom 263 women and 123 men returned completed questionnaires, yielding a response rate of 80·75 %. The final sample of 1183 participants comprised 751 women and 432 men. Proficiency in English was the only exclusion criterion, as the questionnaires were language rich.

Measures

Self-report measures in questionnaire format were presented in two booklets. The first booklet contained questions relating to everyday memory function, as well as demographics and health. The second booklet contained a FFQ designed to assess usual dietary intake.

Memory performance

Perceived everyday memory function was assessed by the memory functioning questionnaire (MFQ)(Reference Gilewski, Zelinski and Schaie33). The MFQ provides an assessment of perceived memory functioning in non-clinical samples. It contains sixty-four items across seven domains which examine the presence of memory problems (one item, maximum score 7), the frequency of common memory problems (eighteen items, maximum score 126), the frequency of poor reading recall (ten items, maximum score 70), the quality of recall (four items, maximum score 28), the seriousness of forgetting (eighteen items, maximum score 126), retrospective functioning (comparison of current memory with past memory function; five items, maximum score 35), and the use of mnemonics (eight items, maximum score 56). Participants rated their responses on a seven-point scale ranging from 1 to 7. Across all domains, except use of mnemonics, higher scores represent higher levels of perceived memory functioning.

Demographics and health

Demographics and health measures included questions about age, years of education, self-rated health (rated 1 =  poor to 5 =  excellent), BMI calculated from self-reported height and weight using the formula weight/(height)2, minutes of exercise (defined as sport) per week, number of cigarettes smoked per d, number of alcoholic (i.e. standard) drinks per week, number of on-going medical conditions, number of currently used medications and number of currently used dietary supplements. These variables have previously been shown to affect cognitive performance(Reference Atkinson, Cesari, Kritchevsky, Penninx, Fried, Guralnik and Williamson34Reference Krahn, Freese, Hauser, Barry and Goodman36), and hence were examined as potential covariates of any associations between dietary intakes of fucose, mannose, galactose, rhamnose, arabinose and xylose, and self-reported memory performance.

Dietary intake

Dietary intake of saccharides was estimated using a self-completed, quantified FFQ(Reference Baghurst and Record37). This took the form of a twenty-page booklet including a list of over 180 common food and beverage items and questions relating to food preparation and dietary habits. Participants indicated how often they consumed each of the listed foods and beverages. Average daily consumption was based on participants' reports of how often a specified standard serving size of each food or beverage item was consumed. For example, intakes of fucose, mannose, galactose, rhamnose, arabinose and xylose were derived from food sources such as flaxseed, cauliflower, Brussels sprouts, legumes, red cabbage and husks of grain, respectively. This information, together with the nutrient composition of the food item per unit weight taken from food tables(38, Reference Paul and Southgate39), allowed participants' daily nutrient intake to be calculated using the FREQUAN dietary analysis program. Such analyses have been shown to adequately capture habitual dietary patterns and to provide an indication of nutritional intake from the diet(Reference Hu, Rimm, Smith-Warner, Feskanich, Stampfer, Ascherio, Sampson and Willett40, Reference Paul, Rhodes, Kramer, Baer and Rumpler41).

Design

A cross-sectional design was used to investigate the links between dietary intake of fucose, mannose, galactose, rhamnose, arabinose and xylose, and self-reported cognition. Intake was calculated as the total of soluble and insoluble amounts of each of these saccharides consumed (μg/d). The dose–response relationship between some nutrient intakes (for example folate, vitamins B12 and B6) and cognition has previously been shown to be non-linear, with moderate intakes associated with better performance(Reference Bryan, Calvaresi and Hughes42). Hence, to be able to identify any non-linear effects of dietary saccharide intake on cognition, dietary intake quartiles for fucose, mannose, galactose, rhamnose, arabinose and xylose were used as the independent variables, with the first quartile reflecting the lowest intake and the fourth reflecting the highest.

Results

Before analysis, distributions of all variables were examined for normality. The data for all variables were normally distributed. ANOVA were conducted to identify demographics and health indicators that differed by fucose, mannose, galactose, rhamnose, arabinose and xylose intake quartiles for possible inclusion as covariates when assessing the effects of intakes on cognition. Post hoc comparisons using Bonferroni procedures were carried out to locate significant differences between intake quartiles, with α set at 0·05. Significant results for each of the saccharides along with descriptive statistics on demographic and health variables are presented in Table 1. Non-significant differences are not presented.

Table 1 Demographic and health measures by saccharide intake quartile

(Mean values and standard deviations)

a,b,c Mean values within a row with unlike superscript letters were significantly different (P < 0·05).

*P < 0·05, **P < 0·01.

As can be seen in Table 1, there were significant effects of fucose, mannose, galactose, rhamnose, arabinose and xylose quartiles for demographic and health indicators. Specifically, post hoc comparisons showed that higher fucose intakes (fourth quartile) were related to smoking fewer cigarettes and consuming less alcohol than low intakes (first quartile), and being in better health compared with moderate intakes (second quartile). Higher intakes of mannose (third and fourth quartiles) were in addition related to having a lower BMI, spending more time exercising and using more dietary supplements than low intakes (first quartile). For galactose, higher intakes were related only to having better self-reported health and drinking less alcohol, with higher intakes of saccharides (fourth quartile) being related to consuming significantly less alcohol than low intakes (first quartile). Higher intakes (fourth quartile) of rhamnose were related to being older, exercising more, consuming less alcohol and being in better health than low intakes (first quartile). Higher intakes (fourth quartile) of arabinose in addition related to having experienced more years of education than low intakes (first quartile). Finally, for xylose, higher intakes (fourth quartile) related to more years of education, and consuming less alcohol than low intakes (first quartile). Therefore, these demographic and background variables that were associated with saccharide intake were used as covariates in the analyses that follow.

Analyses of covariance were performed to determine the effects of dietary intake of fucose, mannose, galactose, rhamnose, arabinose and xylose on self-reported memory performance. Post hoc comparisons using Bonferroni procedures were carried out to locate significant differences between intake quartiles, with α set at 0·05. Only significant results for each saccharide along with descriptive statistics are presented in Table 2. Additionally, regression analyses were carried out to determine the amount of unique variance in self-reported memory functioning explained by each of the saccharides after controlling for the specific covariates.

Table 2 Memory functioning by saccharide intake quartile(Mean values and standard deviations)

a,b,c Mean values within a row with unlike superscript letters were significantly different (P < 0·05).

*P < 0·05, **P < 0·01.

There were significant effects of fucose intake on the frequency of common memory problems and the mnemonics usage subscales of the MFQ, after controlling for time spent exercising, self-rated health, number of cigarettes smoked and number of alcoholic drinks. Post hoc comparisons showed that individuals in the first intake quartile reported more frequent memory problems than those in the second quartile. Individuals in the first intake quartile also reported using mnemonics more frequently than those in the second and third intake quartiles. Fucose intake still explained a significant 0·2 % of the variance in frequency of common memory problems and 0·3 % of the variance in mnemonic usage after controlling for the aforementioned covariates. After controlling for self-rated health, BMI, time spent exercising, number of cigarettes smoked, number of alcoholic drinks and number of dietary supplements, intake of mannose also had a significant effect on the mnemonics usage subscale of the MFQ, with those in the first intake quartile reporting more frequent use of mnemonics than those in the third intake quartile. Mannose intake contributed a further 1·2 % of the variance in mnemonic usage after prior entry of the covariates. Additionally, there were significant effects of galactose intake on the frequency of common memory problems, the frequency of poor reading recall and the retrospective functioning subscales of the MFQ after controlling for self-rated health and alcohol consumption. In particular, individuals in the first and second intake quartiles reported less frequent memory problems than those in the fourth quartile. Individuals in the second intake quartile also compared their current memory more favourably to past memory function than did those in the fourth intake quartile, and reported less frequent poor reading recall than those in the third and fourth intake quartiles. Galactose intake accounted for a further 1·2 % of the variance in frequency of common memory problems, 0·7 % of the variance in frequency of poor reading recall, and 0·7 % of the variance in retrospective functioning beyond that accounted for by the covariates. Furthermore, there were significant effects of rhamnose intake on the mnemonic usage subscale of the MFQ after controlling for age, time spent exercising, number of alcoholic drinks and self-rated health. Specifically, individuals in the first quartile self-reported greater use of mnemonic strategies for memory than those in the second and third quartiles. Rhamnose intake explained an additional 1·3 % of the variance in mnemonic usage over and above that explained by the covariates. Finally, there were no statistically significant effects of xylose on any memory measure, and there was a non-significant trend for an effect of arabinose on mnemonic usage (P = 0·06).

Discussion

The present study assessed the dietary intake of saccharides in middle-aged adults, and examined whether intake was associated with self-reported memory performance. At present there is no recommended daily intake for saccharides. To our knowledge, the present study is the first to report quantified dietary intakes of the saccharides fucose, mannose, galactose, rhamnose, arabinose and xylose, in a population-based sample. Intakes of these saccharides were positively related to indicators of health, such as exercise, smoking and alcohol consumption. This suggests that individuals with higher intakes of saccharides tend to also have other healthy lifestyle habits.

Dietary intakes of fucose, mannose, galactose and rhamnose were related to self-reported memory functioning. In particular, saccharide intake was related to perceived frequency of memory problems, reading recall, retrospective functioning and mnemonics usage. Thus, longer-term intakes of saccharides through the usual diet appear to be positively related to memory functioning. The observed associations between usual dietary intakes of fucose, mannose, galactose, rhamnose and memory functioning are consistent with reports of enhanced learning and memory in animals following supplementation with these saccharides(Reference Krug, Wagner, Staak and Smalla20, Reference Fong, Neff and Hadjiconstantinou22, Reference Wetzel, Popov, Lossner, Schulzeck, Honza and Matthies43), and accord with the proposed mechanism of saccharide effects in the brain. In particular, saccharides have been shown to specifically enhance the cellular mechanism required for the formation of memory traces in hippocampal cells(Reference Matthies, Staak and Krug19). The present findings also concur with a recent study that found positive effects of saccharide intake, estimated from the consumption of saccharide-containing vegetables and fruit, on verbal recall(Reference Best, Kemps and Bryan30).

Overall, moderate intakes of fucose, mannose, galactose and rhamnose (i.e. second and third intake quartiles) were associated with better self-reported memory performance. This suggests that the relationship between saccharide intake and cognition may be non-linear, and would concur with previous reports of non-linear dose–response relationships between various nutrients (for example, folate and B vitamins) and cognitive performance(Reference Bryan and Calvaresi3, Reference Bryan, Calvaresi and Hughes42). Importantly, self-rated memory did not decline, but rather plateaued, at higher saccharide intake levels. Morris et al. (Reference Morris, Evans, Tangney, Bienias and Wilson29) similarly showed minimal differences in rates of cognitive change between the fourth and fifth intake quintiles of vegetable intake.

Intakes of fucose, mannose, galactose and rhamnose continued to explain a significant, albeit small, proportion of the variance in self-reported memory performance after controlling for demographic and health measures, such as exercise, smoking and alcohol consumption. This suggests that dietary saccharide intake contributes to perceived memory functioning over and above any influence of healthy lifestyle indicators. However, because of the complex interactions between nutrients in foods, the present findings could also reflect antioxidant effects. Hence, the present findings need to be followed by randomised controlled intervention studies that allow for greater control over the amount of saccharides consumed and to establish any causal link between saccharide intake and memory functioning.

A potential limitation of the present study is the use of self-report measures to assess memory functioning. Not only do individuals have difficulty accurately judging their cognitive abilities(Reference Dunning, Johnson, Ehrlinger and Kruger44, Reference Mabe and West45), but self-report measures are also prone to social desirability response biases. In addition, correlations between self-report and objective measures of memory are at best moderate(Reference Paulhus, Robinson, Shaver and Wrightman46, Reference Podewils, McLay, Rebok and Lyketsos47). Thus, future investigations into the relationship between dietary saccharide intake and memory might usefully employ more objective indices of memory performance, such as the Wechsler memory scales(Reference Wechsler48) and the Rey auditory-verbal learning test(Reference Rey49).

Acknowledgements

There are no conflicts of interest of any of the authors in the production of this paper.

References

1Dye, L, Lluch, A & Blundell, JE (2000) Macronutrients and mental performance. Nutrition 16, 10211034.CrossRefGoogle ScholarPubMed
2Bryan, J (2004) Mechanisms and evidence for the role of nutrition in cognitive ageing. Aging Int 29, 2845.CrossRefGoogle Scholar
3Bryan, J & Calvaresi, E (2004) Associations between dietary intake of folate and vitamins B-12 and B-6 and self-reported cognitive function and psychological well-being in Australian men and women in midlife. J Nutr Health Aging 8, 226232.Google ScholarPubMed
4Morris, MC, Evans, DA, Bienias, JL, Scherr, PA, Tangney, CC, Hebert, LE, Bennett, DA, Wilson, RS & Aggarwal, H (2004) Dietary niacin and the risk of incident Alzheimer's disease and of cognitive decline. J Neurol Neurosur Psychiatry 75, 10931099.CrossRefGoogle ScholarPubMed
5Best, T, Kemps, E & Bryan, J (2005) Effects of saccharides on brain function and cognitive performance. Nutr Rev 63, 409418.CrossRefGoogle ScholarPubMed
6Dwek, RA (1995) Glycobiology: “towards understanding the function of sugars”. Biochem Soc Trans 23, 125.CrossRefGoogle Scholar
7Alper, J (2001) Searching for medicine's sweet spot. Science 291, 23382343.CrossRefGoogle ScholarPubMed
8Bertozzi, CR & Kiessling, LL (2001) Chemical biology. Science 289, 2357.CrossRefGoogle Scholar
9Ramberg, J & McAnalley, BH (2002) Is saccharide supplementation necessary? GlycoScience and Nutrition (Official Publication of GlycoScience.com: The Nutrition Science Site), May 2002, vol. 3, issue 3..Google Scholar
10Kleene, R & Schachner, M (2004) Glycans and neural cell interactions. Nature Rev Neurosci 5, 195208.CrossRefGoogle ScholarPubMed
11Martin, PT (2002) Glycobiology of the synapse. Glycobiology 12, 1R7R.CrossRefGoogle ScholarPubMed
12Bandtlow, CE & Zimmermann, DR (2000) Proteoglycans in the developing brain: new conceptual insights for old proteins. Physiol Rev 80, 12671290.CrossRefGoogle ScholarPubMed
13Benton, D, Owens, DS & Parker, PY (1994) Blood glucose influences memory and attention in young adults. Neuropsychologia 32, 595607.CrossRefGoogle ScholarPubMed
14Riby, LM (2004) The impact of age and task domain on cognitive performance: a meta-analytic review of the glucose facilitation effect. Brain Impair 5, 145165.CrossRefGoogle Scholar
15Craft, S, Murphy, C & Wemstrom, J (1994) Glucose effects on complex memory and nonmemory tasks: the influence of age, sex and glucoregulatory response. Psychobiology 22, 95105.CrossRefGoogle Scholar
16Donahoe, RT & Benton, D (2000) Glucose tolerance predicts performance on tests of memory and cognition. Physiol Behav 71, 395401.CrossRefGoogle Scholar
17Hall, JL, Gonder-Frederick, LA, Chewning, WW, Silveria, J & Gold, PE (1989) Glucose enhancement of performance on memory tests in young and aged adults. Neuropsychologia 27, 11291138.CrossRefGoogle Scholar
18Sunram-Lea, SL, Foster, JK, Durlach, P & Perez, C (2001) Glucose facilitation of cognitive performance in healthy young adults: examination of the influence of fast-duration, time of day and pre-consumption plasma glucose levels. Psychopharmacology 157, 4654.Google ScholarPubMed
19Matthies, H, Staak, S & Krug, M (1996) Fucose and fucosyllactose enhance in-vitro hippocampal long-term potentiation. Brain Res 725, 276280.CrossRefGoogle ScholarPubMed
20Krug, M, Wagner, M, Staak, S & Smalla, K (1994) Fucose and fucose-containing sugar epitopes enhance hippocampal long-term potentiation in the freely moving rat. Brain Res 643, 130135.CrossRefGoogle ScholarPubMed
21Rose, PR (1995) Glycoproteins and memory formation. Behav Brain Res 66, 7378.CrossRefGoogle ScholarPubMed
22Fong, TG, Neff, NH & Hadjiconstantinou, M (1997) GM1 ganglioside improves spatial learning and memory of aged rats. Behav Brain Res 85, 203211.CrossRefGoogle ScholarPubMed
23Marquardt, T, Luehn, K, Srikrishna, G, Freeze, HH, Harms, E & Vestweber, D (1999) Correction of leukocyte adhesion deficiency type II with oral fucose. Blood 94, 39763985.CrossRefGoogle ScholarPubMed
24Benton, EW (1997) Case report: observed improvements in developmental dyslexia accompanied by supplementation with glyconutrients and phytonutrients. J Am Nutraceutical Assoc, Suppl. 1, 1315.Google Scholar
25Dykman, KD & Briggs, J (1997) The effects of nutritional supplementation on alcoholics: mood states and craving for alcohol. J Am Nutraceutical Assoc, Suppl. 1, 811.Google Scholar
26Wang, C, Pivik, RT & Dykman, RA (2002) Effects of a Glyconutritional Supplement on Resting Brain Activity. Federation Proceedings: Experimental Biology Meeting, 20–24 April, 2002, New Orleans, LA. Vol. 16, issue 4–5, p. 1012. Bethesda, MD: The Federation of American Societies for Experimental Biology.Google Scholar
27Wang, C, Szabo, JS & Dykman, RA (2004) Effects of a carbohydrate supplement upon resting brain activity. Integr Physiol Behav Sci 39, 126138.CrossRefGoogle ScholarPubMed
28Best, T, Bryan, J & Burns, N (2008) An investigation of the effects of saccharides on the memory performance of middle-aged adults. J Nutr Health Aging (In the Press).CrossRefGoogle ScholarPubMed
29Morris, MC, Evans, DA, Tangney, CC, Bienias, JL & Wilson, RS (2006) Association of vegetable and fruit consumption with age-related cognitive change. Neurology 67, 13701376.CrossRefGoogle ScholarPubMed
30Best, T, Kemps, E & Bryan, J (2007) A role for dietary saccharide intake in cognitive performance. Nutr Neurosci 10, 113120.CrossRefGoogle ScholarPubMed
31McDaniel, MA, Maier, SF & Einstein, GO (2002) “Brain specific” nutrients: a memory cure? Psychol Sci Publ Interest 3, 1238.CrossRefGoogle ScholarPubMed
32Nicolas, A-S, Nourhashemi, LF, Lanzmann-Petithory, D & Vellas, B (2001) Nutrition and cognitive function. Nutr Clin Care 4, 156167.CrossRefGoogle Scholar
33Gilewski, MJ, Zelinski, EM & Schaie, KW (1990) The memory functioning questionnaire for assessment of memory complaints in adulthood and old age. Psychol Aging 5, 482490.CrossRefGoogle ScholarPubMed
34Atkinson, HH, Cesari, M, Kritchevsky, SB, Penninx, BWJH, Fried, LP, Guralnik, JM & Williamson, JD (2005) Predictors of combined cognitive and physical decline. J Am Geriatr Soc 53, 11971202.CrossRefGoogle ScholarPubMed
35Johnson, J (1999) Alcohol, hypertension and cognitive decline. Br J Psychiatry 175, 91.CrossRefGoogle ScholarPubMed
36Krahn, D, Freese, J, Hauser, R, Barry, K & Goodman, B (2003) Alcohol use and cognition at mid-life: the importance of adjusting for baseline cognitive ability and educational attainment. Alcohol Clin Exp Res 27, 11621166.CrossRefGoogle ScholarPubMed
37Baghurst, KI & Record, SJ (1984) A computerised dietary analysis system for use with diet diaries or food frequency questionnaires. Community Health Stud 8, 1118.CrossRefGoogle ScholarPubMed
38Health DoCSa (1992) Composition of Foods Australia. Canberra: Australian Government Publishing Service.Google Scholar
39Paul, AA & Southgate, DA (1978) McCance and Widdowson's The Composition of Foods, 4th ed.Amsterdam: Elsevier.Google Scholar
40Hu, FB, Rimm, E, Smith-Warner, SA, Feskanich, D, Stampfer, MJ, Ascherio, A, Sampson, L & Willett, WC (1999) Reproducibility and validity of dietary patterns assessed with a food-frequency questionnaire. Am J Clin Nutr 69, 243249.CrossRefGoogle ScholarPubMed
41Paul, DR, Rhodes, DG, Kramer, M, Baer, DJ & Rumpler, WV (2005) Validation of a food frequency questionnaire by direct measurement of habitual ad libitum food intake. Am J Epidemiol 162, 806814.CrossRefGoogle ScholarPubMed
42Bryan, J, Calvaresi, E & Hughes, D (2002) Short-term folate, vitamin B-12 or vitamin B-6 supplementation slightly affect memory performance but not mood in women of various ages. J Nutr 132, 13451356.CrossRefGoogle Scholar
43Wetzel, W, Popov, N, Lossner, B, Schulzeck, S, Honza, R & Matthies, H (1980) Effect of l-fucose on brain protein metabolism and retention of a learned behavior in rats. Pharmacol Biochem Behav 13, 765771.CrossRefGoogle ScholarPubMed
44Dunning, D, Johnson, K, Ehrlinger, J & Kruger, J (2003) Why people fail to recognise their own incompetence. Curr Dir Psychol Sci 12, 8387.CrossRefGoogle Scholar
45Mabe, PA & West, SG (1982) Validity of self-evaluation of ability: a review and meta-analysis. J Appl Psychol 67, 280296.CrossRefGoogle Scholar
46Paulhus, DL (1991) Measurement and control of response bias. In Measures of Personality and Social Psychological Attitudes, pp. 1759 [Robinson, JP, Shaver, PR and Wrightman, LS, editors]. New York: Academic Press.CrossRefGoogle Scholar
47Podewils, LJ, McLay, RN, Rebok, GW & Lyketsos, CG (2003) Relationship of self-perceptions of memory and worry to objective measures of memory and cognition in the general population. Psychosomatics 44, 461470.CrossRefGoogle ScholarPubMed
48Wechsler, D (1997) Wechsler Memory Scale, 3rd ed.New York: The Psychological Corporation.Google Scholar
49Rey, A (1964) L'Examen Clinique en Psychologie (Clinical Examination in Psychology). Paris: Presses Universitaires de France.Google Scholar
Figure 0

Table 1 Demographic and health measures by saccharide intake quartile(Mean values and standard deviations)

Figure 1

Table 2 Memory functioning by saccharide intake quartile(Mean values and standard deviations)