1
Centre INSERM U897-Epidemiologie-Biostatistique, University of Bordeaux, ISPED, Bordeaux, F-33000, France
2
Centre INSERM U897-Epidemiologie-Biostatistique, INSERM, ISPED, Bordeaux, F-33000, France
3
Québec Center of Excellence on Aging, CHU de Québec Research Center, Quebec City, QC G1S 4L8, Canada
4
Faculty of Pharmacy, Laval University, Quebec City, QC G1V 0A6, Canada
5
Département de Nutrition, Université de Montréal, Montréal, QC H3T 1A8, Canada
6
Centre de Recherche, Institut Universitaire de Gériatrie de Montréal, CIUSSS du Centre-est-de-l’Île-de-Montréal, Montréal, QC H3W 1W5, Canada
7
Department of Medicine, University of Montreal, Montreal, QC H3C 3J7, Canada
8
Centre Hospitalier de l’Université de Montréal Research Center (CRCHUM), Montréal, QC H2X 0A9, Canada
9
Research Center on Aging—Centre Intégré Universitaire de Santé et des Services Sociaux de l’Estrie—Centre Hospitalier Universitaire de Sherbrooke (CIUSS de l’Estrie-CHUS), Sherbrooke, QC J1H 4C4, Canada
10
Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
†
These authors contributed equally to this work.
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Abstract
Background: Dietary and nutrient patterns have been linked to health outcomes related to aging. Food intake is influenced by environmental and genetic factors. The aim of the present study was to compare nutrient patterns across two elderly populations sharing a common ancestral
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Background: Dietary and nutrient patterns have been linked to health outcomes related to aging. Food intake is influenced by environmental and genetic factors. The aim of the present study was to compare nutrient patterns across two elderly populations sharing a common ancestral cultural background, but living in different environments.
Methods: The diet quality, lifestyle and socioeconomic characteristics of participants from the Three-City Study (3C, France,
n = 1712) and the Québec Longitudinal Study on Nutrition and Successful Aging (NuAge, Quebec, Canada,
n = 1596) were analyzed. Nutrient patterns and their food sources were identified in the two samples using principal component analysis. Diet quality was compared across sample-specific patterns by describing weekly food intake and associations with the Canadian Healthy Eating Index (C-HEI).
Results: Three nutrient patterns were retained in each study: a healthy, a Western and a more traditional pattern. These patterns accounted for 50.1% and 53.5% of the total variance in 3C and NuAge, respectively. Higher education and non-physical occupations over lifetime were associated with healthy patterns in both studies. Other characteristics such as living alone, having a body mass index lower than 25 and being an ex-smoker were associated with the healthy pattern in NuAge. No association between these characteristics and the nutrient patterns was noted in 3C. The healthy and Western patterns from each sample also showed an inverse association with C-HEI.
Conclusion: The two healthy patterns showed important similarities: adequate food variety, consumption of healthy foods and associations with common sociodemographic factors. This work highlights that nutrient patterns derived using
a posteriori methods may be useful to compare the nutritional quality of the diet of distinct populations.
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