Diet quality and nutrient density in subjects with metabolic syndrome: Influence of socioeconomic status and lifestyle factors. A cross-sectional assessment in the PREDIMED-Plus study.

Background: Socioeconomic disparities and lifestyle factors are likely to determine the overall quality of the diet. In addition, overeating is compatible with inadequate micronutrient intake and it can lead to adverse health outcomes.

Objective: To assess adequacy of dietary nutrient intake and to investigate the influence of socioeconomic and lifestyle factors on nutrient density in a large primary cardiovascular prevention trial conducted in healthy participants with metabolic syndrome (MetS) to assess the cardiovascular effects of an energy-restricted Mediterranean diet (PREDIMED-Plus).

[Mediterranean and Western dietary patterns in adult population of a Mediterranean area; a cluster analysis].

Objective: To identify dietary patterns among participants in a representative nutritional survey in the Valencia Community, and to analyze the association with socio-demographic characteristics and lifestyles.

Methods: Data for this study were from 1803 participants (973 women) in the Nutrition and Health Survey conducted in 1994 on a representative sample of adult population of Valencia Community. Diet was assessed by a validated food frequency questionnaire.

[Validation of self-reported weight and height university population and factors associated with differences between self reported and measured antropometrics].

Introduction: Obesity is an important public health problem related to a higher risk of death from chronic degenerative diseases such as diabetes, cardiovascular diseases and several types of cancer. In epidemiological studies of big sample size, only self-reported weight and height can be collected for feasibility reasons and body mass index (BMI) estimates may be questioned.

Objectives: In this study we compare self-reported and measured weight, height and BMI in a mostly young population of university students, and explore factors associated with discrepancies between self-reported and measured data.