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See detailStability-based validation of dietary patterns obtained by cluster analysis
Sauvageot, Nicolas ULiege; Schritz, Anna; Alkerwi, Ala'a et al

in Nutrition Journal (2017), 16(3),

Abstract Background Cluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have ... [more ▼]

Abstract Background Cluster analysis is a data-driven method used to create clusters of individuals sharing similar dietary habits. However, this method requires specific choices from the user which have an influence on the results. Therefore, there is a need of an objective methodology helping researchers in their decisions during cluster analysis. The objective of this study was to use such a methodology based on stability of clustering solutions to select the most appropriate clustering method and number of clusters for describing dietary patterns in the NESCAV study (Nutrition, Environment and Cardiovascular Health), a large population-based cross-sectional study in the Greater Region (N = 2298). Methods Clustering solutions were obtained with K-means, K-medians and Ward’s method and a number of clusters varying from 2 to 6. Their stability was assessed with three indices: adjusted Rand index, Cramer’s V and misclassification rate. Results The most stable solution was obtained with K-means method and a number of clusters equal to 3. The “Convenient” cluster characterized by the consumption of convenient foods was the most prevalent with 46% of the population having this dietary behaviour. In addition, a “Prudent” and a “Non-Prudent” patterns associated respectively with healthy and non-healthy dietary habits were adopted by 25% and 29% of the population. The “Convenient” and “Non-Prudent” clusters were associated with higher cardiovascular risk whereas the “Prudent” pattern was associated with a decreased cardiovascular risk. Associations with others factors showed that the choice of a specific dietary pattern is part of a wider lifestyle profile. Conclusion This study is of interest for both researchers and public health professionals. From a methodological standpoint, we showed that using stability of clustering solutions could help researchers in their choices. From a public health perspective, this study showed the need of targeted health promotion campaigns describing the benefits of healthy dietary patterns. [less ▲]

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See detailUse of finite mixture models in dietary patterns analysis.
Sauvageot, Nicolas ULiege; Schritz, Anna; Leite, Sonia et al

Scientific conference (2016, September 29)

Background In recent years, the dietary pattern approach has been used extensively to describe overall eating profiles in populations. In the literature, dietary patterns are often computed by cluster ... [more ▼]

Background In recent years, the dietary pattern approach has been used extensively to describe overall eating profiles in populations. In the literature, dietary patterns are often computed by cluster analysis and principal component analysis (PCA). However, PCA does not create distinct groups of individuals with different dietary habits; moreover the choice of the clustering method and of the number of clusters in cluster analysis remains difficult. On the other hand, finite mixture models (FMM) do not have those limitations and have many other advantages. However, they have been rarely used in dietary pattern analysis. Objective The objective of this study was to use FMM to compute dietary patterns based on data from the NESCaV survey (Nutrition, Environment and Cardiovascular Health), a large population-based study carried out between 2007 and 2011among the Greater Region population (N=2298 subjects). Methods A 134-food frequency questionnaire was used to assess dietary intakes. The most appropriate parameterization of the covariance matrix and number of clusters was chosen on the basis of the Bayesian information criterion (BIC). Results Four dietary patterns were determined. A ”non-prudent” and a “prudent” patterns were characterized respectively by non-healthy and healthy food choices. A “breakfast/low alcohol” pattern was characterized by high intakes of food items usually consumed at breakfast. Finally, a “vegetables/dairy products/low carbohydrate” pattern was characterized by low intakes of carbohydrates but high intakes of vegetables, pulses, fruits, animal protein and fat mostly from dairy products. The “non-prudent” pattern was the most prevalent with 34% of the population assigned to this cluster. The “prudent”, “breakfast/low alcohol” and “vegetables/dairy products/low carbohydrate” patterns accounted respectively for 25%, 29% and 19% of the population, respectively. Women, older people and non-smokers followed the “prudent” and “breakfast/low alcohol”, whereas the “non-prudent” and “vegetables/dairy products/low carbohydrate” were more adopted by men and smokers. In addition, the “non-prudent” pattern was associated with higher cardiovascular risk. Conclusion FMM should be considered more often as they do not have limitations encountered with other methods and are not restrictive on cluster geometry. Moreover, this study highlights the need for targeted health promotion campaigns focussing on the benefits of healthy dietary patterns. [less ▲]

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See detailComparaison de deux méthodes statistiques explorant la relation entre régimes alimentaires et risques cardiovasculaires.
Sauvageot, Nicolas ULiege; Leite, Sonia; Donneau, Anne-Françoise ULiege et al

Poster (2016, September)

Introduction L’analyse en composantes principales (ACP) et la régression à rangs réduits (RRR) sont deux méthodes de réduction de dimension permettant de construire des variables reflétant des régimes ... [more ▼]

Introduction L’analyse en composantes principales (ACP) et la régression à rangs réduits (RRR) sont deux méthodes de réduction de dimension permettant de construire des variables reflétant des régimes alimentaires. Les régimes alimentaires obtenus par ACP sont associés aux habitudes alimentaires de la population étudiée tandis que ceux obtenus par RRR sont associés à des indicateurs d’intérêt. L’objectif de cette étude est de comparer les deux approches quant aux régimes alimentaires obtenus et à leurs associations avec les facteurs de risques cardiovasculaires (FRCV). Méthodologie Les données proviennent de l’étude interrégionale et transversale nutrition, environnement et santé cardiovasculaire (NESCAV) ayant pour but de décrire la santé cardiovasculaire de la grande région (Luxembourg, Lorraine et Wallonie). Les apports alimentaires ont été mesurés à l’aide d’un questionnaire de fréquence alimentaire et 2298 individus ont été retenus pour cette analyse. Les indicateurs d’intérêt retenus pour l’approche RRR sont les FRCV usuels (obésité, hypertension, diabète, dyslipidémie). Résultats Nous avons trouvé que les régimes alimentaires consommés par la population et ceux associés au FRCV étaient similaires. Les régimes riches en fruits, fruits secs et oléagineux, légumes, huile d’olive, graisse riche en oméga 6, thé, et ceux pauvres en aliments frits, viandes, charcuteries, soda, plats préparés, bières étaient associés à une diminution des FRCV. Les autres régimes caractérisés par des apports élevés en aliments frits, viandes, abats, bières, vins, apéritifs et liqueurs et de faibles apports en céréales, sucres et soda étaient associés à une augmentation des FRCV. Conclusions L’utilisation des deux méthodes est utile pour obtenir des informations permettant d’élaborer de nouvelles recommandations alimentaires. Les régimes alimentaires identifiés dans cette étude sont à la fois associés aux habitudes alimentaires de la population et aux FRCV. [less ▲]

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See detailAssociation of Empirically Derived Dietary Patterns with Cardiovascular Risk Factors: A Comparison of PCA and RRR Methods
Sauvageot, Nicolas ULiege; Leite, sonia; Alkerwi, Ala'a et al

in PLoS ONE (2016), 11(8),

Abstract Introduction Principal component analysis is used to determine dietary behaviors of a population whereas reduced rank regression is used to construct disease-related dietary patterns. This study ... [more ▼]

Abstract Introduction Principal component analysis is used to determine dietary behaviors of a population whereas reduced rank regression is used to construct disease-related dietary patterns. This study aimed to compare both types of DP and theirs associations with cardiovascular risk factors (CVRF). Materiel and Methods Data were derived from the cross sectional NESCAV (Nutrition, Environment and Cardiovascular Health) study, aiming to describe the cardiovascular health of the Greater region’s population (Grand duchy of Luxembourg, Wallonia (Belgium), Lorraine (France)). 2298 individuals were included for this study and dietary intake was assessed using a 134-item food frequency questionnaire. Results We found that CVRF-related patterns also reflect eating behaviours of the population. Comparing concordant food groups between both dietary pattern methods, a diet high in fruits, oleaginous and dried fruits, vegetables, olive oil, fats rich in omega 6 and tea and low in fried foods, lean and fatty meat, processed meat, ready meal, soft drink and beer was associated with lower prevalence of CVRF. In the opposite, a pattern characterized by high intakes of fried foods, meat, offal, beer, wine and aperitifs and spirits, and low intakes of cereals, sugar and sweets and soft drinks was associated with higher prevalence of CVRF. Conclusion In sum, we found that a “Prudent” and “Animal protein and alcohol” patterns were both associated with CVRF and behaviourally meaningful. Moreover, the relationships of those dietary patterns with lifestyle characteristics support the theory that food choices are part of a larger pattern of healthy lifestyle. [less ▲]

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See detaildietary patterns in the NESCaV study
Sauvageot, Nicolas ULiege

Speech/Talk (2016)

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See detailUse of finite mixture models for dietary patterns analysis
Sauvageot, Nicolas ULiege; Albert, Adelin ULiege; alkerwi, alaa et al

Conference (2014, August 25)

Free-living individuals have multifaceted diets and consume foods in numerous combinations. The effect of the overall diet beyond that of single foods can be studied with dietary pattern analysis ... [more ▼]

Free-living individuals have multifaceted diets and consume foods in numerous combinations. The effect of the overall diet beyond that of single foods can be studied with dietary pattern analysis. Furthermore, the dietary pattern approach reduces data-dimensionality and alleviates problems of model over-fitting and residual confounding that occur with the statistical analysis of many food items. Most recent dietary pattern analyses have used factor and cluster analysis. We describe a finite mixture modelling (FMM) approach for dietary pattern analysis and show its advantages over previous ones. First, FMM allows estimating pattern prevalence directly from the model parameters as opposed to the subjective joint classification of the factors. Moreover, in contrast to 'hard' assignment of clustering methods, FMM also produces posterior cluster membership probabilities for each subject providing measures of uncertainty of the associated classification. Second, it allows problems in determining the number of clusters and choosing an appropriate clustering method to be recast as statistical model choice problems. Third, it allows for covariates adjustment simultaneously with the fitting process and the size of pattern to depend on a set of concomitant variables. Additionally, FMM is invariant to linear transformation, for example standardization. We discuss these advantages and illustrate the approach with an analysis of the NESCAV (Nutrition, environment and cardiovascular health) dataset (Alkerwi et al, 2010) and show how identified dietary patterns and their associated uncertainty can be used to predict disease. [less ▲]

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See detaildilemmas in cluster analysis
Sauvageot, Nicolas ULiege

Conference (2013, November 27)

Cluster analysis is a set of multivariate procedures to detect natural groupings in data. The objective of those methods is to group a set of objects in such a way that objects in the same group (called ... [more ▼]

Cluster analysis is a set of multivariate procedures to detect natural groupings in data. The objective of those methods is to group a set of objects in such a way that objects in the same group (called cluster) are more similar to each other than to those in other groups. Organizing data into sensible groupings arises naturally in many scientific fields as psychology, biology, statistics, bioinformatics, marketing, and so on. However, the obtained solution is not unique and it strongly depends upon the analyst’s choices. Representation and normalization scheme, selection of distance measures and a clustering algorithm, choice of the number of clusters and their interpretations are all subjective choices which change the final output. Those decisions are mainly guided by the purpose of grouping, domain knowledge and the individual data set. Therefore, cluster validity assessment should be performed to evaluate the validity of the obtained clusters and to find the partitioning that best fits the underlying data. I provide a brief overview of clustering, summarize well known algorithms, and discuss the major challenges and key issues in performing clustering analysis. [less ▲]

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See detailON THE RELATIONSHIP BETWEEN DIETARY PATTERNS AND CARDIOVASCULAR RISK FACTORS IN THE GREATER REGION POPULATION
Sauvageot, Nicolas ULiege; Alkerwi, Alaa; Zannad, Faiez et al

Conference (2013, October 25)

Abstract Background: The prevalence of chronic pathologies such as cardio-vascular diseases is increasing, in part due to dietary habits. Some dietary patterns may influence health more than individual ... [more ▼]

Abstract Background: The prevalence of chronic pathologies such as cardio-vascular diseases is increasing, in part due to dietary habits. Some dietary patterns may influence health more than individual foods, nutrients or food groups. The objective of this research was to identify dietary patterns associated with common cardiovascular risk factors (CVRF) in a sample of adult individuals living in the Greater Region. Methods: Data were taken from the cross-sectional NESCAV (Nutrition, Environment and Cardiovascular Health) study, aiming to describe the cardiovascular health of the Greater Region’s population (1). Dietary intake was assessed using a 132-item food frequency questionnaire (FFQ), from which 44 food groups were formed. Food group consumptions were adjusted for energy intake using the residuals method of Willet and Stampfer (2). Participants under a special diet to manage their CVRF were excluded. Likewise, those who had a history of cardiovascular disease or with confirmed diabetes, hypertension, and/or dyslipidemia were also discarded as they may have changed their diet. Thus, a total of 1691 individuals were included in the study (865 from Luxembourg, 527 from Wallonia and 299 from Lorraine). We applied the reduced rank regression method to identify specific dietary patterns strongly associated with common CVRF (3). The CVRF-specific dietary patterns were constructed by choosing intake data as predictors and CVRF as outcomes. Nine CVRF (BMI, waist to hip ratio, total cholesterol, triglycerides, HDL cholesterol, LDL cholesterol, blood glucose, diastolic and systolic blood pressure) were used in the statistical analysis. Associations between dietary patterns and CVRF were adjusted according to gender, age, smoking status and level of physical activity. Results: Two main dietary patterns were identified. A pattern characterized by high intakes of alcohol, potatoes and high-fat food such as pastries, fried foods, offal, processed and smoked meat, margarine, but low intakes of cereals, soups, soft drink and olive oil, was significantly associated with an increase of all CVRF. On the other hand, a healthy pattern characterized by high consumption of brown bread, nuts, soups, vegetables, smoked and canned fish, olive oil and oil rich in omega 6 and 3, high-fat dairy products, butter and margarine, but a low consumption of fried foods, rice/pasta, meat, ready meal, soft drink and beer, was associated with a decrease of all CVRF except LDL. Conclusions: Our results suggest that dietary patterns of the Greater Region population are related to CVRF. Diet rich in alcohol and high-fat food is associated with a higher cardiovascular risk whereas a healthy diet is associated with a lower cardiovascular risk. These results emphasize the need for cross-border preventive nutritional strategies. [less ▲]

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See detailValidation of the Food Frequency Questionnaire Used to Assess the Association between Dietary Habits and Cardiovascular Risk Factors in the NESCAV Study
Sauvageot, Nicolas ULiege; Guillaume, Michèle ULiege; Albert, Adelin ULiege et al

in Journal of Food Science (2013), 3(3),

Abstract Background: In epidemiological studies, the validation of dietary assessment instruments is important to avoid biased associations with outcome measures. Objective: Our objective was to assess ... [more ▼]

Abstract Background: In epidemiological studies, the validation of dietary assessment instruments is important to avoid biased associations with outcome measures. Objective: Our objective was to assess the validity of the 134-item food frequency questionnaire (FFQ) used in the Nutrition Environment and Cardiovascular Health (NESCAV) study. Methods: The FFQ was validated against a 3-day dietary record (DR) on a sample of 29 women. The intra- class correlation coefficient (ICC) and Bland and Altman plots were used to assess absolute agreement, whereas relative agreement was appraised by Spearman’s correlation coefficient and Cohen kappa coefficient based on cross classification of 3-category nutrient intake. Results: The two methods differed significantly for the majority of micronutrients with FFQ yielding higher intakes than the DR. The bias between the two methods was nonetheless acceptable with an average overestimation by the FFQ of 11% for macronutrients and 29% for micronutrients. Regarding precision, results differed by 48% for micronutrients and 50% for macronutrients. Correlations on energy-adjusted data by the two methods were satisfactory with an average correlation of 0.47 and 16/25 coefficients above 0.40. Only vitamin A and cholesterol showed poor correlations of 0.02 and 0.05, respectively. On average, the correct classification rate in 3 categories was 50.3% and 19/25 kappa coefficients were above 0.20. Poor agreement was found for protein, cholesterol, starch, vitamins A, B12 and E with weighted kappa coefficient less than 0.20. Conclusion: Although absolute values of dietary intakes were not always accurate, the relationship and agreement between FFQ and DR may be considered as satisfactory. In particular, the FFQ was able to categorize subjects into 3 broad categories of intakes for most nutrients. Results for proteins, cholesterol, starch, vitamins A, E and B12 however ought to be interpreted with caution [less ▲]

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See detailUse of food frequency questionnaire to assess relationships between dietary habits and cardiovascular risk factors in NESCAV study: validation with biomarkers
Sauvageot, Nicolas ULiege; alkerwi, alaa; Albert, Adelin ULiege et al

in Nutrition Journal (2013), 12(143),

Abstract Background: Validation of Food frequency questionnaire (FFQ) is particularly important element, as incorrect information may lead to false associations between dietary factors and diseases. The ... [more ▼]

Abstract Background: Validation of Food frequency questionnaire (FFQ) is particularly important element, as incorrect information may lead to false associations between dietary factors and diseases. The aim of the study was to evaluate the validity of the FFQ used in NESCAV (Nutrition, Environment and Cardiovascular Health) study, by comparing the estimated intakes of fruits and vegetables and of several micro-nutrients with corresponding nutritional biomarkers. Methods: Relative validity was assessed in a sample of 922 subjects (452 men and 470 women). Comparisons between FFQ-estimates and their corresponding biomarkers were performed through correlation and cross classification into quintiles by using both crude and energy-adjusted FFQ-estimates. Correlations adjusted for confounders were also computed. All analyses were performed separately for men and women. Results: Concerning micro-nutrients, significant correlations were found for vitamin B9, D, E, B12 β -carotene and iodine in both men and women. Energy-adjustment led to an increase of all correlations cited previously. However, after excluding supplement users, correlations for vitamin D were not significant anymore. Concerning fruits and vegetables, all correlations were significant. Vegetables alone and fruits and vegetables correlated better in men (r around 0.2) than in women (r around 0.1). In men, correlation was also better for vegetables alone and fruits and vegetables than fruits alone. Conclusion: These data demonstrate that this FFQ is a reasonable tool to assess intakes of fruits and vegetables and of several micro-nutrients. We conclude that our FFQ is suitable to be used in NESCAV study, although protein and vitamin D estimates should be interpreted with caution [less ▲]

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See detailValidation par biomarqueurs d’un FFQ permettant d’étudier le lien entre alimentation et risques cardiovasculaires
Sauvageot, Nicolas ULiege; Alkerwi, Alaa; Donneau, Anne-Françoise ULiege et al

Poster (2012, September)

Introduction La recherche sur l'alimentation et son lien avec les maladies nécessite une collecte rigoureuse des données nutritionnelles permettant d'estimer avec précision l'apport nutritionnel. Le « ... [more ▼]

Introduction La recherche sur l'alimentation et son lien avec les maladies nécessite une collecte rigoureuse des données nutritionnelles permettant d'estimer avec précision l'apport nutritionnel. Le « Food Frequency Questionnaire (FFQ) » a été choisie pour étudier le lien entre alimentation et risques cardiovasculaires dans un échantillon représentatif de la Grande région recruté pour l’étude NESCAV (Nutrition, environnement et santé cardio-vasculaire). Objectif Valider le FFQ utilisé à l’aide de biomarqueurs afin d’évaluer son habilité à estimer correctement les habitudes alimentaires. Méthodes Afin de prendre en compte les spécificités de la Grande région et le volet cardio-vasculaire, la liste d’items d’un FFQ existant a été modifiée et élargie. Tous les nutriments calculés à partir du FFQ ont été ajustés par rapport à l’énergie par la méthode des résidus. La comparaison des nutriments calculés par le FFQ et les bio-marqueurs correspondants a été faite par le calcul des coefficients de corrélation avec ajustement sur plusieurs facteurs confondants. L’accord entre les deux méthodes a été estimé par le calcul des pourcentages de concordance et du coefficient Kappa. Résultats La validation s’est effectuée sur un échantillon de 466 sujets (236 hommes et 241 femmes). Des corrélations significatives ont été observées pour les folates, le β-carotène dans les deux sexes et pour la vitamine B12 et l’iode chez les femmes. Discussion Ces résultats sont comparables à ceux d’études précédentes. Les corrélations sont souvent expliquées par le fait que les nutriments du FFQ représentent la quantité ingérée alors que les biomarqueurs représentent la quantité absorbée par le corps. [less ▲]

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