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Nutrients. 2019 Aug 5;11(8). pii: E1808. doi: 10.3390/nu11081808.

Nutrient Patterns, Cognitive Function, and Decline in Older Persons: Results from the Three-City and NuAge Studies.

Author information

1
University Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France. b.alles@eren.smbh.univ-paris13.fr.
2
Faculté de Pharmacie, Laval University, Québec, QC G1V 0A6, Canada. b.alles@eren.smbh.univ-paris13.fr.
3
Centre d'excellence sur le vieillissement de Québec, Centre de recherche du CHU de Québec, Institut sur le vieillissement et la participation sociale des aînés (IVPSA), Québec, QC G1S 4L8, Canada. b.alles@eren.smbh.univ-paris13.fr.
4
Centre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL-UL), Québec, QC G1J 0A4, Canada. b.alles@eren.smbh.univ-paris13.fr.
5
Equipe de Recherche en Epidémiologie Nutritionnelle, Centre de Recherche en Epidémiologie et Statistiques, Université Paris 13, Inserm (U1153), Inra (U1125), Cnam, Université de Paris, 93017 Bobigny, France. b.alles@eren.smbh.univ-paris13.fr.
6
University Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219, F-33000 Bordeaux, France.
7
Culture et Diffusion des Savoirs EA-7440, University Bordeaux, F-33000 Bordeaux, France.
8
Centre d'excellence sur le vieillissement de Québec, Centre de recherche du CHU de Québec, Institut sur le vieillissement et la participation sociale des aînés (IVPSA), Québec, QC G1S 4L8, Canada.
9
Centre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL-UL), Québec, QC G1J 0A4, Canada.
10
Département de Nutrition, Université de Montréal, Québec and Centre de recherche, Institut universitaire de gériatrie de Montréal, QC H3T 1A8, Canada.
11
Department of Medicine, University of Montreal and Centre Hospitalier de l'Université de Montréal Research Center (CRCHUM), Montréal, QC H3T 1J4, Canada.
12
Canadian Consortium on Neurodegeneration in Aging-Nutrition, Exercise and Lifestyle Team, Montréal, H3T 1E2, Canada.
13
Département de Nutrition, Université de Montréal, Québec and Research Centre, Montreal Heart Institute, Montréal, QC H1T 1C8, Canada.
14
Faculté de Pharmacie, Laval University, Québec, QC G1V 0A6, Canada.

Abstract

Dietary patterns, or the combination of foods and beverages intake, have been associated with better cognitive function in older persons. To date, no study has investigated the link between a posteriori nutrient patterns based on food intake, and cognitive decline in longitudinal analyses. The aim of this study was to evaluate the relationship between nutrient patterns and cognitive function and decline in two longitudinal cohorts of older persons from France and Canada. The study sample was composed of participants from the Three-City study (3C, France) and the Quebec Longitudinal Study on Nutrition and Successful Aging (NuAge, Quebec, Canada). Both studies estimated nutritional intakes at baseline, and carried out repeated measures of global cognitive function for 1,388 and 1,439 individuals, respectively. Nutrient patterns were determined using principal component analysis methodology in the two samples, and their relation with cognitive function and decline was estimated using linear mixed models. In 3C, a healthy nutrient pattern, characterized by higher intakes of plant-based foods, was associated with a higher global cognitive function at baseline, as opposed to a Western nutrient pattern, which was associated with lower cognitive performance. In NuAge, we also found a healthy nutrient pattern and a Western pattern, although no association was observed with either of these patterns in the Canadian cohort. No association between any of the nutrient patterns and cognitive decline was observed in either cohort. There is a need for longitudinal cohorts focusing on nutrient patterns with substantial follow-up, in order to evaluate more accurately associations between nutrition and cognition in older persons.

KEYWORDS:

aging; cognition; diet; nutrients; nutrition; principal component analysis

PMID:
31387312
DOI:
10.3390/nu11081808
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