Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-20T13:02:37.224Z Has data issue: false hasContentIssue false

Long-term association of food and nutrient intakes with cognitive and functional decline: a 13-year follow-up study of elderly French women

Published online by Cambridge University Press:  10 February 2009

Marie-Noël Vercambre
Affiliation:
INSERM (Institut National de la Santé et de la Recherche Médicale), ERI 20, EA 4045, and Institut Gustave Roussy, VillejuifF-94805, France INSERM, U888, Montpellier, F-34093 France; Univ Montpellier1, MontpellierF-34000, France
Marie-Christine Boutron-Ruault
Affiliation:
INSERM (Institut National de la Santé et de la Recherche Médicale), ERI 20, EA 4045, and Institut Gustave Roussy, VillejuifF-94805, France
Karen Ritchie
Affiliation:
INSERM, U888, Montpellier, F-34093 France; Univ Montpellier1, MontpellierF-34000, France
Françoise Clavel-Chapelon*
Affiliation:
INSERM (Institut National de la Santé et de la Recherche Médicale), ERI 20, EA 4045, and Institut Gustave Roussy, VillejuifF-94805, France
Claudine Berr
Affiliation:
INSERM, U888, Montpellier, F-34093 France; Univ Montpellier1, MontpellierF-34000, France
*
*Corresponding author: Dr Françoise Clavel-Chapelon, fax +33 1 42 11 40 00, email clavel@igr.fr
Rights & Permissions [Opens in a new window]

Abstract

The objective of the present study was to determine the potential long-term impact of dietary habits on age-related decline among 4809 elderly women (born between 1925 and 1930) in the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, a French epidemiological cohort. In 1993, an extensive diet history self-administered questionnaire was sent to all participants, and in 2006 another questionnaire on instrumental activities of daily living (IADL) and recent cognitive change was sent to a close relative or friend of each woman. Logistic models adjusted for socio-demographic, lifestyle and health factors were performed to evaluate associations between habitual dietary intakes and two outcomes of interest based on the informant response: recent cognitive decline and IADL impairment. Recent cognitive decline was associated with lower intakes of poultry, fish, and animal fats, as well as higher intakes of dairy desserts and ice-cream. IADL impairment was associated with a lower intake of vegetables. The odds of recent cognitive decline increased significantly with decreasing intake of soluble dietary fibre and n-3 fatty acids but with increasing intake of retinol. The odds of IADL impairment increased significantly with decreasing intakes of vitamins B2, B6 and B12. These results are consistent with a possible long-term neuroprotective effect of dietary fibre, n-3 polyunsaturated fats and B-group vitamins, and support dietary intervention to prevent cognitive decline.

Type
Full Papers
Copyright
Copyright © The Authors 2009

Age-related cognitive decline is an important public health concern, with a prevalence that is rapidly increasing with population ageing. Cognitive impairment leads to significant functional loss and is a major component of total age-related deterioration(Reference McGuire, Ford and Ajani1). In the absence of curative treatments, prevention has become a real challenge. Several risk factors are known to be involved in the aetiology of cognitive impairment(Reference Blennow, de Leon and Zetterberg2), but few are modifiable, among them nutrition. Longitudinal studies investigating dietary influence on cognitive outcomes in the elderly have suggested that increased intakes of specific vitamins or minerals could be associated with a reduced incidence of cognitive impairment(Reference Gillette-Guyonnet, Van Kan and Andrieu3). To explain these results, different hypotheses involving oxidative stress, or inflammatory or vascular pathways have been put forward. However, the long-term relationship between diet and cognitive decline remains unclear and even conflicting. A better understanding of dietary factors that contribute to the maintenance of cognitive ability is thus of high priority(Reference Ortega, Requejo and Andres4). The importance of prospective studies of specifically long duration, which would include subjects whose diet was monitored long before cognitive assessment, has previously been stressed(Reference Gonzalez-Gross, Marcos and Pietrzik5). Using longitudinal data from the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (Epidemiological Study of Women of MGEN) (E3N) study, we examined the associations between previous usual diet and age-related cognitive impairment.

Subjects and methods

The ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ cohort

The E3N cohort includes 98 995 French women within the National Education System, born between 1925 and 1950. This ongoing prospective study primarily investigates cancer risk factors(Reference Touillaud, Thiebaut and Fournier6) in women, with particular focus on diet and hormones. The research programme was approved by the Bicêtre Hospital Review Board and the French National Commission for Data Protection and Privacy. All study participants gave informed consent and, since June 1990, they have been asked at approximately 24-month intervals to complete self-administered questionnaires on medical events and a variety of lifestyle characteristics.

The ageing sub-cohort of the Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale study

In 2006, a specific ageing survey was carried out. Of the 98 995 women in the cohort, those who where born between 1925 and 1930 (n 10 040) represented the target population, because of the higher prevalence of cognitive impairment in this stratum than in middle-aged women. Among these 10 040 elderly women, 1095 were deceased or had dropped out. Therefore, the ageing survey involved 8945 cohort participants. A questionnaire intended for a close relative or friend of the E3N participant was designed to obtain indirect data on cognitive and functional problems faced by the elderly women. The questionnaire was sent in January 2006. It included eight instrumental activities of daily living (IADL)(Reference Katz7) and the ‘DEtérioration Cognitive Observée’ (observed cognitive deterioration) (DECO) scale(Reference Ritchie and Fuhrer8). While IADL items provide a comprehensive view of the functional consequences of cognitive decline in everyday life (telephone use, shopping, mode of transportation, ability to handle personal medication, finance handling, food preparation, housekeeping, laundry), DECO provides more specific information on cognitive functioning observed by informants over the past year. This nineteen-item Likert scale allows the evaluation of recent cognitive decline through alterations of the capacity to perform specific tasks related to memory, attention, and visuospatial and language skills.

A questionnaire from a relative was obtained for 5941 participants (66·4 %). Functional and cognitive data were complete for a total of 5839 women. Because of missing or non-physiologically plausible dietary data – the exposure of interest, assessed in 1993 – the analysis sample finally included 4809 elderly women. Dietary data were considered as non-physiologically plausible when the calculated ratio of energy intake to energy requirement fell in the highest or lowest percentile for the entire cohort(Reference Ferrari, Slimani and Ciampi9).

Outcomes of interest (2006)

In order to explore the nutrition–cognition relationship, we examined two aspects of cognitive functioning, based on informant report: cognitive decline over a period of 1 year and cognitive status as reflected by current impact on everyday functioning.

Recent cognitive decline was defined on the basis of the DECO score (range 0–38), according to a threshold of 33. This cut-off point has been previously shown to distinguish subjects with a high risk of progressive pathological decline in a French general population sample, with a sensitivity of 89 % and a specificity of 67 %(Reference Ritchie and Fuhrer10). The individuals with a DECO score under 33 constituted the group of recent cognitive decliners.

The functional dimension of age-related decline was based on a simplified IADL scale, which has been previously validated(Reference Barberger-Gateau, Fabrigoule and Helmer11): for each woman, we calculated the 4-IADL score by summing up the number of limitations to the subject's ability to use the telephone, take her medications, use public transport and manage her own budget. The women with a non-null 4-IADL score constituted the group of functional decliners (sensitivity of 62 % and specificity of 80 % for cognitive troubles).

Dietary assessment (1993)

Dietary data were collected in 1993 with an extensive diet history questionnaire covering daily consumption of 208 foods and beverages. The dietary questionnaire was sent with a booklet of photographs to facilitate estimation of portion sizes. Both the questionnaire and the illustrated booklet had been previously validated(Reference van Liere, Lucas and Clavel12, Reference Lucas, Niravong and Villeminot13) on a sample of 115 women, taking the average of twelve 24 h dietary recalls obtained at monthly intervals over a 1-year period as reference. Average daily dietary intakes of macro- and micronutrients were estimated based on dietary questionnaire data, and using a food composition table derived from the French national database(Reference Favier, Ireland-Ripert and Toque14). A high proportion of subjects (76 % for foods and 72 % for nutrients on average) were classified in the same or adjacent quintiles for the dietary questionnaire and 24 h recalls. Among the analysis sample, mean age at dietary assessment was 65·5 (sd 1·8) years.

Potential confounders

Socio-economic factors, lifestyle and medical background have been associated with cognitive ageing(Reference Fratiglioni, Paillard-Borg and Winblad15). To limit confounding effects in analyses, adjustment variables included socio-demographic characteristics (age in 2006 as 76–79 v. 80–82 years; education level as < 12 years v. ≥ 12 years), BMI ( < 18·5 kg/m2; 18·5–24·9 kg/m2; 25–29·9 kg/m2; ≥ 30 kg/m2), an indicator of average physical activity based on the median value in metabolic equivalents per week ( ≤ 50; >50), the quartiles of average dietary energy intake in kJ/d, as well as smoking status (current or past smoker; non-smoker). Supplement consumption was taken into account (use of vitamin D and/or Ca, use of other vitamins or minerals). Other self-reported variables related to medical follow-up were use of postmenopausal hormones (ever; never), diabetes mellitus (ever; never), hypertension (ever; never) and hypercholesterolaemia (ever; never). Adjustment variables also included self-reported history of CHD (myocardial infarction or angina pectoris), stroke, cancer and depression. Data on cancer were validated through pathological reports, as the main outcome of the E3N study.

Missing values

Missing values for educational level, BMI, supplement consumption, physical activity and smoking status represented less than 5 % of subjects for each of these covariates. Thus, we replaced them by the modal value. This procedure is routinely used when analysing E3N data for adjustment categorical variables, in order to include all subjects with non-missing data for the main outcomes/exposures, so as to limit bias and power loss due to too many excluded cases. However, we verified that results of statistical models were globally unchanged when subjects with one or more missing values for any of these variables were excluded from the analyses (restricted sample of 4515 subjects).

Statistical analyses

To illustrate the link between cognitive and functional status as appraised by the informant, we performed kernel density estimation(Reference Silverman16) of the DECO score according to the 4-IADL score. This analysis was conducted among the 4758 women for whom both scores were computable. We studied bivariate associations between potential confounders and the two outcomes of interest: DECO score < 33 and 4-IADL score >0. All variables listed above as potential confounders were then included in models assessing nutritional factors.

Dietary habits were approached by considering successively daily intakes of food groups (for example, vegetables, fish, eggs), macronutrients (for example, carbohydrates, proteins) and micronutrients (for example, vitamins and minerals). Raw intakes of food groups as well as residuals on energy(Reference Willett, Howe and Kushi17) of nutrient intakes were categorised into tertiles according to the distribution in our elderly population, except when food groups were consumed by less than 10 % of the sample. In those cases (i.e. legumes; pizza, sandwiches and snacks; beef, pork and lamb; poultry; offal; animal fats; dairy desserts and ice-cream; sugar and confectionery; pastries and cakes; coffee; tea; soups; wine; beer; other alcoholic drinks), we isolated a category of non-consumers, and considered consumers in two groups according to the median consumption. Although alcohol is a nutrient, it was categorised as described above for rarely consumed food groups, since 13·8 % of women in our sample showed null intake.

We used multivariable logistic regression to compute the OR and 95 % CI. Each nutritional factor considered was entered into separate logistic regression models. Tests for linear trend were performed using the ordinal score on categories of nutritional intake.

Except for the kernel density estimation, which was computed with R software version 2.3.0 (http://www.r-project.org), all analyses were performed using SAS software (version 9.1; SAS Institute, Inc., Cary, NC, USA). All results were considered significant at the 5 % level. All statistical tests were two-sided.

Results

Sample selection

Compared with women for whom no relative responded, women for whom informant data were obtained in 2006 were somewhat younger and more educated. They were also more likely to be married and to have responded to the dietary questionnaire sent in 1993. In addition, women excluded from the analysis sample because of missing dietary data were less educated than the investigated population.

Characteristics of women according to their cognitive and functional status

Among the 4758 women included in the analysis sample, 518 women had a DECO score < 33 (12·4 %), 716 had a 4-IADL score >0 (14·9 %) and 268 presented both declines (5·6 %). Although non-interchangeable, functional status and recent cognitive decline were closely related in our sample, as illustrated by Fig. 1, which simultaneously represents DECO score distributions in subjects with the 4-IADL score respectively equal to 0, 1, 2, 3 or 4. While the maximum score on the DECO scale is 38 and the minimum is 0 (with lower scores indicating a sharper decrease in cognitive performance), DECO cut-off points for the first, second and third quartiles were, respectively: 36, 38 and 38 for women without disability; 32, 35 and 37 for women who had one IADL impairment; 28, 33 and 36 for women who had two IADL impairments; 23, 27 and 34 for women who had three IADL impairments; 10, 17 and 28 for women who had four IADL impairments.

Fig. 1 Cognitive decline and functional impairment. Kernel density estimation of the ‘Détérioration Cognitive Observée’ (observed cognitive deterioration) questionnaire (DECO) score according to the Instrumental Activities of Daily Living (IADL) score in the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 2006. The 4-IADL score is defined as the number of limitations to the subject's ability to use the telephone, take medication, use public transport and manage her own budget. The analysis was conducted among the 4758 subjects for whom both scores were computable. (—), 4-IADL score = 0 (n 4093); (– – –), 4-IADL score = 1 (n 493); (---), 4-IADL score = 2 (n 88); (·-·-·), 4-IADL score = 3 (n 35); (·–·–·), 4-IADL score = 4 (n 49).

Characteristics of women as a function of their cognitive and functional status are described in Table 1. Recent cognitive decline was positively associated with age, history of depression, cancer, CHD, stroke and diabetes mellitus, but inversely associated with education level and physical activity level. IADL impairment was associated with higher age, lower education level, BMI ≥ 25 kg/m2, lower energy intake, never-smoker status, lower level of physical activity, non-use of supplements and non-use of postmenopausal hormones. IADL impairment was also positively associated with history of depression, CHD, stroke, diabetes mellitus and hypertension.

Table 1 Comparison of elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006, depending on their cognitive and functional status

DECO, ‘Détérioration Cognitive Observée’ (observed cognitive deterioration) questionnaire; IADL, instrumental activities of daily living.

* P values obtained through univariate logistic regression analyses.

Missing values were replaced by the most frequent modality (variables with less than 5 % missing values).

Except energy from alcohol.

§ Myocardial infarction or angina pectoris.

Dietary intakes and age-related decline

Results of multi-adjusted logistic models that tested associations between age-related decline and habitual dietary intakes of twenty-five food-groups are shown in Table 2. After controlling for various potential factors, women with recent cognitive decline consumed in the past significantly lower amounts of poultry, fish, and animal fats. They also consumed higher amounts of dairy desserts and ice-cream. The association between higher odds of cognitive decline and higher intake of pastries and cakes was borderline significant. Women with IADL impairment had lower intake of vegetables.

Table 2 Multi-adjusted odds ratios of habitual dietary habits (assessed in 1993) associated with cognitive decline or instrumental activities of daily living (IADL) impairment (assessed in 2006) in elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006*

DECO, ‘Détérioration Cognitive Observée’ (observed cognitive deterioration) questionnaire.

* Through multi-adjusted logistic regression models, taking healthy elderly as the reference group. Adjustment was made on all covariates listed in Table 1. Each food group was considered separately.

Group 1, group 2 and group 3 were defined as tertile 1, tertile 2 and tertile 3 of food intake unless otherwise indicated.

Mean and sd were calculated using the whole sample.

§ Group 1, group 2 and group 3 were defined as no consumption, consumption ≤ median and consumption>median.

Results of multi-adjusted logistic models that tested associations between age-related decline and habitual dietary intakes of thirty-three macro- or micronutrients are shown in Table 3. The odds of recent cognitive decline increased with decreasing intake of total dietary fibre, soluble dietary fibre and of n-3 fatty acids, while they increased with increasing intake of retinol. Furthermore, recent cognitive decliners showed a higher n-6:n-3 fatty acid ratio than women with a DECO score ≥  33. Concerning functional status, the odds of IADL impairment increased significantly with decreasing intake of vitamin B2, B6 and B12.

Table 3 Multi-adjusted odds ratios of habitual nutrient intakes (assessed in 1993) associated with cognitive decline or instrumental activities of daily living (IADL) impairment (assessed in 2006) in elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006*

DECO, ‘Détérioration Cognitive Observée’ (observed cognitive deterioration) questionnaire.

* Through multi-adjusted logistic regression models, taking healthy elderly as the reference group. Adjustment was made on all covariates listed in Table 1. Each nutrient was considered separately.

Group 1, group 2 and group 3 were defined as tertile 1, tertile 2 and tertile 3 of intake residuals on energy (except for alcohol).

Mean and sd were calculated using the whole sample.

§ Because of the non-negligible percentage of abstainers and the specificity of this group, the population was split into abstainers (13·8 %), 0 < mean intake ≤ 8·3 g/d (43·5 %) and mean intake >8·3 g/d (42·7 %).

Interactions, sensitivity analysis and alternate analysis

We verified that modification of cut-off points for adjustment variables had no effect on the final results. For example, the 80-year cut-off point was chosen for age for easier comparison, as it is a symbolic threshold, but use of 78 years (the median value), as the cut-off did not substantially modify the overall findings, nor did any sensitivity analysis using different cut-off values.

We tested potential interactions between dietary intakes and age or education level, but none yielded significant differential effects.

In order to test the stability of the present results, we used a more restrictive definition of cognitive decline using a cut-off point of 31 rather than 33 for the DECO score, which resulted in 341 women with recent cognitive decline v. 4468 control women. Associations between informant-appraised cognitive status and dietary intake remained quite stable for most nutrients. However, the association with n-3 fatty acids was no longer statistically significant, even though this nutrient still displayed a similar inverse association with cognitive decline (OR 0·93 (95 % CI 0·70, 1·22) and 0·88 (95 % CI 0·67, 1·15) for tertiles 2 and 3 respectively, taking the first tertile of intake as reference).

To rule out a possible confounding effect of dietary supplement use, we conducted our analyses in a restricted sample (n 3347), excluding all women who declared taking at least one type of supplement. Associations involving lower intakes of vitamin C became statistically significant with higher odds of both cognitive decline and functional impairment. No other difference was found in this sub-sample compared with those obtained for the whole sample (data not tabulated).

Furthermore, we tested the stability of the present results when including all women with available dietary data: women with extreme values for the energy intake:energy requirement ratio were reintegrated in the sample analysis (n 4922). The set of significant associations remained unchanged in this larger sample. For example, regarding soluble dietary fibre and DECO score < 33 (n 622 cases in this larger sample), OR for the second and third tertiles of intake (v. the first tertile) were respectively 0·92 (95 % CI 0·75, 1·13) and 0·76 (95 % CI 0·61, 0·94), as compared with women with a high DECO score.

Discussion

In 2006, elderly women participating in the E3N cohort that were reported by informants to have undergone recent cognitive decline had, 13 years previously, lower intakes of poultry, fish, and animal fats, as well as higher intakes of dairy desserts and ice-cream. They had lower habitual intakes of dietary fibre and n-3 fatty acids, but a higher intake of retinol. Furthermore, elderly women that were reported by informants to be functionally impaired had, in the past, lower intakes of vegetables and vitamins B2, B6 and B12.

The main interest of the present study lies in the time interval (more than a decade) between dietary assessment and cognitive and functional assessment, which enabled us to explore the long-term effect of dietary habits in ageing. Although diet is likely to vary throughout life, our hypothesis is that it remains quite stable after menopause and retirement, but before the advanced state of ageing processes. Because these women were aged 62–68 years at the time of dietary assessment, nutritional data considered in the present study seem to be informative when relating long-term individual dietary habits to late-life outcome. Moreover, the nutritional data of the E3N cohort have provided meaningful results when studying associations between usual dietary intake and cancer occurrence, a disease that may also have a latency period of many years before being diagnosed(Reference Touillaud, Thiebaut and Fournier6, Reference Touvier, Kesse and Clavel-Chapelon18). Finally, the life-course approach to age-related disorders provided opportunities for identifying the nature and timing of environmental contributions(Reference Whalley, Dick and McNeill19), which is not possible in a short-term design study.

Another strength of the present study lies in the availability of extensive adjustment data. Careful control for potential confounders is important in an observational setting so as to limit biases that may arise, since socio-economic status and other behavioural and medical characteristics may influence both dietary intake and cognitive function. In the present study, we were able to implement fully adjusted models. In particular, the association between dietary intake and cognitive decline remained significant after controlling for various vascular factors (hypertension, hypercholesterolaemia, diabetes mellitus, CHD and stroke), suggesting that diet may influence cognitive ageing through pathways that are partly separate from cardiovascular processes.

In this large epidemiological study, cognitive assessment was based on informant self-response to validated questionnaires (IADL and DECO) rather than face-to-face interviews. Substantial data support the validity of using both functional and informant measures in ageing studies(Reference Tierney, Herrmann and Geslani20). More precisely, DECO, which is independent of socio-economic background(Reference Ritchie and Fuhrer10), has been recently reported to be a good screening device for evaluating cognitive decline due to multiple causes(Reference Cullen, O'Neill and Evans21). In addition, the 4-IADL score has proven to be a valid indicator of cognitive loss and is highly predictive of early dementia(Reference Barberger-Gateau, Fabrigoule and Helmer11). Descriptive analyses showed relationships between our outcomes of interest and characteristics usually associated with cognitive and functional impairment (age, education level, history of stroke, etc), thus supporting our definitions for testing hypotheses in the research field on age-related decline.

Outcome information analysed in the present study was informant-reported, perhaps leading to some misclassification, but there is no reason to suspect differential errors.

Missing values in dietary data or in cognitive information may lead to a selection of the study sample. Indeed, exclusion of women with non-available dietary data resulted in over-representation of younger and more educated women. These observations are consistent with the hypothesis that non-responders are more likely to undergo adverse outcomes or to be less health-conscious(Reference Goldberg, Chastang and Zins22). Such a selection may influence study results in two ways: by decreasing the statistical power and by masking some of the effects of nutritional intake, since the cognitive impact of some nutritional deficiencies may have been underestimated because of an insufficient range of exposure in the selected analysis sample. In particular, several epidemiological studies found an association with fruit consumption, vitamin C, vitamin E or β-carotene intake, in agreement with the antioxidant hypothesis. In our sample, we observed only a borderline association between cognitive decline and lower vitamin C intake. The limited range of intake in our population, with few women having low consumption levels in foods rich in antioxidant components, may explain the absence of certain associations in the present study. For example, over 95 % of the elderly E3N participants consumed more than one 80 g portion of fruit daily, with a median intake of 350 g/d. As a comparison, the fruit consumption level was quite lower in another French cohort showing a significant protective association involving fruit and dementia: in the ‘three-City cohort’ study, more than 20 % of the participants ate less than one daily serving of fruit(Reference Barberger-Gateau, Raffaitin and Letenneur23).

Another limitation is that our sample includes only women, which precludes generalising the present results to men, who have on the whole different food intake and nutritional status(Reference Hercberg, Czernichow and Galan24).

Our findings of significant associations between age-related decline and lower long-term intake of certain specific nutrients – namely n-3 fatty acids, dietary fibre and vitamin B6 – have already been described, generally in studies with shorter prospective design(Reference Luchsinger and Mayeux25). However, the present study is not in complete agreement with previous ones in that it shows that higher intake of retinol and lower intake of animal fats were both associated with cognitive decline. Potential explanations for these unexpected results include confounding effects and chance resulting from multiple analyses. Regarding residual confounding, a null intake of animal fats could be, for instance, an indicator of poor general health (similar to alcohol abstinence), thus explaining that a low intake of animal fats was related to an increased OR of cognitive decline. Moreover, in the studied sample, 70 % of animal fats was butter and intake level was generally low, with 95 % of the studied women consuming less than 20 g/d (median intake 6 g/d). As a comparison, 90 % of the population included in the Chicago Health and Aging Project consumed more than 16 g animal fat/d (Reference Morris, Evans and Bienias26). This latter study concluded that a diet high in saturated fat might be associated with cognitive decline among older individuals. The intake range in the E3N population could thus be below the level where saturated fat becomes deleterious.

Regarding chance due to multiple analyses, we performed nearly sixty models for each outcome of interest. Nutritional epidemiology, especially when dealing with large-scale studies such as ours, is restricted by both the fact that multiple analyses are performed (often leading to separate reports for each category of foods or nutrients), and that misclassification of the diet results in a decreased power of the studies(Reference Willett27). Thus very few, if any, use the Bonferroni correction, which would most often lead to no significant association at all. Restricting analyses to variables already described in the literature, such as vitamins and fatty acids, would limit the opportunity to explore novel hypotheses, although more emphasis should be made on findings consistent with the literature. New findings, such as the association with retinol, need to be further confirmed.

Several neuropathogenic mechanisms can be evoked as underlying biological processes for the observed associations. n-3 Fatty acids, in which fish is rich, act on heart and brain not only through the vascular pathway but also through different cellular mechanisms: heart rhythm; neurotransmission; neuroprotection; neurogenesis. Similarly, some B vitamins and homocysteine can act directly on brain cell functioning. Anti-inflammatory and antioxidant properties are suggested to account for the inverse association with dietary fibre and vegetables. On the whole, a number of experimental studies, and a variety of partly common mechanisms, support a favourable effect of these compounds.

Although underlying biological pathways are not yet fully elucidated, the present study nonetheless has public health implications along with previous studies(Reference Luchsinger, Noble and Scarmeas28). The present results suggest that prevention of age-related impairment may be reached through a balanced diet rich in vegetables, fish and poultry, and limited in sweet dairy products, not only in later life but starting in middle age. These recommendations, also suggested for cancer(29) and cardiovascular protection(Reference De Caterina, Zampolli and Del Turco30), may enhance the quality of life(Reference Kennedy31).

Our large-scale longitudinal study with validated dietary data may represent a valuable contribution to a better understanding of the link between long-term nutrition and late-life cognition. The present results support the hypothesis that high intakes of n-3 fatty acids, dietary fibre and some B-group vitamins may contribute to a reduction in age-related impairment.

Acknowledgements

The E3N cohort is supported by the French League against Cancer, the European Community, 3M Company, Mutuelle Générale de l'Education Nationale (MGEN), French Institute of Health and Medical Research, Gustave Roussy Institute and several general councils in France. M.-N. V. receives a grant from the Statlife Company and the ‘Association Nationale de la Recherche Technique’. None of the funding agencies played a role in the design or conducting of the study, analysis or interpretation of data, nor in preparation and approval of the manuscript.

F. C.-C. is the principal investigator of the E3N Cohort Study and took responsibility for the integrity of the data. M.-N. V. conducted the statistical analysis, interpreted the data and drafted the manuscript. M.-C. B.-R., K. R., F. C.-C. and C. B. contributed to the writing and revisions. C. B. supervised the statistical analyses. All authors critically reviewed the manuscript.

The authors report no conflict of interest.

References

1McGuire, LC, Ford, ES & Ajani, UA (2006) Cognitive functioning as a predictor of functional disability in later life. Am J Geriatr Psychiatry 14, 3642.CrossRefGoogle ScholarPubMed
2Blennow, K, de Leon, MJ & Zetterberg, H (2006) Alzheimer's disease. Lancet 368, 387403.CrossRefGoogle ScholarPubMed
3Gillette-Guyonnet, S, Van Kan, GA, Andrieu, S, et al. (2007) IANA task force on nutrition and cognitive decline with aging. J Nutr Health Aging 11, 132152.Google ScholarPubMed
4Ortega, RM, Requejo, AM, Andres, P, et al. (1997) Dietary intake and cognitive function in a group of elderly people. Am J Clin Nutr 66, 803809.CrossRefGoogle Scholar
5Gonzalez-Gross, M, Marcos, A & Pietrzik, K (2001) Nutrition and cognitive impairment in the elderly. Br J Nutr 86, 313321.CrossRefGoogle ScholarPubMed
6Touillaud, MS, Thiebaut, AC, Fournier, A, et al. (2007) Dietary lignan intake and postmenopausal breast cancer risk by estrogen and progesterone receptor status. J Natl Cancer Inst 99, 475486.CrossRefGoogle ScholarPubMed
7Katz, S (1983) Assessing self-maintenance: activities of daily living, mobility, and instrumental activities of daily living. J Am Geriatr Soc 31, 721727.CrossRefGoogle ScholarPubMed
8Ritchie, K & Fuhrer, R (1992) A comparative study of the performance of screening tests for senile dementia using receiver operating characteristics analysis. J Clin Epidemiol 45, 627637.CrossRefGoogle ScholarPubMed
9Ferrari, P, Slimani, N, Ciampi, A, et al. (2002) Evaluation of under- and overreporting of energy intake in the 24-hour diet recalls in the European Prospective Investigation into Cancer and Nutrition (EPIC). Public Health Nutr 5, 13291345.CrossRefGoogle ScholarPubMed
10Ritchie, K & Fuhrer, R (1996) The validation of an informant screening test for irreversible cognitive decline in the elderly: performance characteristics within a general population sample. Int J Geriatr Psychiatry 11, 149156.3.0.CO;2-5>CrossRefGoogle Scholar
11Barberger-Gateau, P, Fabrigoule, C, Helmer, C, et al. (1999) Functional impairment in instrumental activities of daily living: an early clinical sign of dementia? J Am Geriatr Soc 47, 456462.CrossRefGoogle ScholarPubMed
12van Liere, MJ, Lucas, F, Clavel, F, et al. (1997) Relative validity and reproducibility of a French dietary history questionnaire. Int J Epidemiol 26, Suppl. 1, S128S136.CrossRefGoogle ScholarPubMed
13Lucas, F, Niravong, M, Villeminot, S, et al. (1995) Estimation of food portion size using photographs: validity, strength, weaknesses and recommendations. J Hum Nutr Diet 8, 6574.CrossRefGoogle Scholar
14Favier, JC, Ireland-Ripert, J, Toque, C, et al. (1995) Répertoire Général des Aliments. Table de Composition (Food Composition Table). Paris: TEC & DOC.Google Scholar
15Fratiglioni, L, Paillard-Borg, S & Winblad, B (2004) An active and socially integrated lifestyle in late life might protect against dementia. Lancet Neurol 3, 343353.CrossRefGoogle ScholarPubMed
16Silverman, BW (1986) Density Estimation. London: Chapman and Hall.Google Scholar
17Willett, WC, Howe, GR & Kushi, LH (1997) Adjustment for total energy intake in epidemiologic studies. Am J Clin Nutr 65, 1220S1228S.CrossRefGoogle ScholarPubMed
18Touvier, M, Kesse, E, Clavel-Chapelon, F, et al. (2005) Dual association of β-carotene with risk of tobacco-related cancers in a cohort of French women. J Natl Cancer Inst  97, 13381344.CrossRefGoogle Scholar
19Whalley, LJ, Dick, FD & McNeill, G (2006) A life-course approach to the aetiology of late-onset dementias. Lancet Neurol 5, 8796.CrossRefGoogle Scholar
20Tierney, MC, Herrmann, N, Geslani, DM, et al. (2003) Contribution of informant and patient ratings to the accuracy of the mini-mental state examination in predicting probable Alzheimer's disease. J Am Geriatr Soc 51, 813818.CrossRefGoogle Scholar
21Cullen, B, O'Neill, B, Evans, JJ, et al. (2007) A review of screening tests for cognitive impairment. J Neurol Neurosurg Psychiatry 78, 790799.CrossRefGoogle ScholarPubMed
22Goldberg, M, Chastang, JF, Zins, M, et al. (2006) Health problems were the strongest predictors of attrition during follow-up of the GAZEL cohort. J Clin Epidemiol 59, 12131221.CrossRefGoogle ScholarPubMed
23Barberger-Gateau, P, Raffaitin, C, Letenneur, L, et al. (2007) Dietary patterns and risk of dementia: the Three-City cohort study. Neurology 69, 19211930.CrossRefGoogle ScholarPubMed
24Hercberg, S, Czernichow, S & Galan, P (2006) Antioxidant vitamins and minerals in prevention of cancers: lessons from the SU.VI.MAX study. Br J Nutr 96, Suppl. 1, S28S30.CrossRefGoogle ScholarPubMed
25Luchsinger, JA & Mayeux, R (2004) Dietary factors and Alzheimer's disease. Lancet Neurol 3, 579587.CrossRefGoogle ScholarPubMed
26Morris, MC, Evans, DA, Bienias, JL, et al. (2004) Dietary fat intake and 6-year cognitive change in an older biracial community population. Neurology 62, 15731579.CrossRefGoogle Scholar
27Willett, W (1998) Nutritional Epidemiology. New York, Oxford: Oxford University Press.CrossRefGoogle Scholar
28Luchsinger, JA, Noble, JM & Scarmeas, N (2007) Diet and Alzheimer's disease. Curr Neurol Neurosci Rep 7, 366372.CrossRefGoogle ScholarPubMed
29World Cancer Research Fund & American Institute for Cancer Research (2007) Nutrition, Physical Activity and the Prevention of Cancer: a Global Perspective. Washington, DC: AICR.Google Scholar
30De Caterina, R, Zampolli, A, Del Turco, S, et al. (2006) Nutritional mechanisms that influence cardiovascular disease. Am J Clin Nutr 83, 421S426S.CrossRefGoogle ScholarPubMed
31Kennedy, ET (2006) Evidence for nutritional benefits in prolonging wellness. Am J Clin Nutr 83, 410S414S.CrossRefGoogle ScholarPubMed
Figure 0

Fig. 1 Cognitive decline and functional impairment. Kernel density estimation of the ‘Détérioration Cognitive Observée’ (observed cognitive deterioration) questionnaire (DECO) score according to the Instrumental Activities of Daily Living (IADL) score in the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 2006. The 4-IADL score is defined as the number of limitations to the subject's ability to use the telephone, take medication, use public transport and manage her own budget. The analysis was conducted among the 4758 subjects for whom both scores were computable. (—), 4-IADL score = 0 (n 4093); (– – –), 4-IADL score = 1 (n 493); (---), 4-IADL score = 2 (n 88); (·-·-·), 4-IADL score = 3 (n 35); (·–·–·), 4-IADL score = 4 (n 49).

Figure 1

Table 1 Comparison of elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006, depending on their cognitive and functional status

Figure 2

Table 2 Multi-adjusted odds ratios of habitual dietary habits (assessed in 1993) associated with cognitive decline or instrumental activities of daily living (IADL) impairment (assessed in 2006) in elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006*

Figure 3

Table 3 Multi-adjusted odds ratios of habitual nutrient intakes (assessed in 1993) associated with cognitive decline or instrumental activities of daily living (IADL) impairment (assessed in 2006) in elderly women (n 4809) of the ‘Etude Epidémiologique de Femmes de la Mutuelle Générale de l'Education Nationale’ (E3N) study, France, 1993–2006*