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See detailStability-based validation of dietary patterns obtained by cluster analysis
Sauvageot, Nicolas ULg; 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 detailScreening for the metabolic syndrome in subjects with migraine
Streel, Sylvie ULg; Donneau, Anne-Françoise ULg; Dardenne, Nadia ULg et al

in Cephalalgia : An International Journal of Headache (2016)

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See detailUse of finite mixture models in dietary patterns analysis.
Sauvageot, Nicolas ULg; 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 detailOne-year Prevalence of Migraine Using a Validated Extended French Version of the ID MigraineTM: a Belgian Population-Based Study
Schoenen, Jean ULg; Streel, Sylvie ULg; Donneau, Anne-Françoise ULg et al

in Cephalalgia : An International Journal of Headache (2015, May), 35(6), 155-156

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See detailValidation of an extended French version of ID MigraineTM as a migraine-screening tool
Streel, Sylvie ULg; Donneau, Anne-Françoise ULg; Dardenne, Nadia ULg et al

in Cephalalgia : An International Journal of Headache (2015), 35(5), 437-442

Introduction: Migraine has a considerable social, economic, physical and emotional burden but remains underdiagnosed and undertreated. A specific migraine screening tool could help remove barriers to ... [more ▼]

Introduction: Migraine has a considerable social, economic, physical and emotional burden but remains underdiagnosed and undertreated. A specific migraine screening tool could help remove barriers to health care and be an attractive instrument for epidemiological studies. The objective of this work was to assess the validity of an extended French version of ID MigraineTM as a migraine-screening tool. Methods: Sixty-seven subjects from the NESCaV study (2010–2012) completed the migraine screen and were diagnosed by a neurologist specializing in headache medicine using the International Classification of Headache Disorders, 2nd edition criteria (gold standard). Agreement between the two diagnoses was evaluated by Cohen kappa coefficient (k). Sensitivity, specificity and predictive values of the migraine screen were calculated. Results: Migraine was diagnosed in 21 (31.3%) of the 67 subjects according to the screening tool and in 24 (35.8%) by the neurologist (k¼0.90). The prevalence of migraine was unrelated to age, gender, education and perception of financial resources. Sensitivity and specificity of the screen were 87.5% and 100%, respectively. The screen prevalence of migraine with aura was 10.4% (sensitivity and specificity: 83.3% and 96.7%, respectively). Conclusion: The extended French version of ID MigraineTM (ef-ID Migraine) is a validated tool to screen migraine in French-speaking countries. [less ▲]

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See detailPrevalence of cardiovascular risk factors in Wallonia (Belgium): results from the NESCaV study
Streel, Sylvie ULg; Donneau, Anne-Françoise ULg; Hoge, Axelle ULg et al

in European Journal of Public Health (2013, November)

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See detailVitamin D coverage among adults in Wallonia (Belgium): findings from the NESCaV study
Hoge, Axelle ULg; Donneau, Anne-Françoise ULg; Streel, Sylvie ULg et al

in European Journal of Public Health (2013, November), 23

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