Analysis of Dietary Pattern Impact on Weight Status for Personalised Nutrition through On-Line Advice: The Food4Me Spanish Cohort

Abstract

Obesity prevalence is increasing. The management of this condition requires a detailed analysis of the global risk factors in order to develop personalised advice. This study is aimed to identify current dietary patterns and habits in Spanish population interested in personalised nutrition and investigate associations with weight status. Self-reported dietary and anthropometrical data from the Spanish participants in the Food4Me study, were used in a multidimensional exploratory analysis to define specific dietary profiles. Two opposing factors were obtained according to food groups’ intake: Factor 1 characterised by a more frequent consumption of traditionally considered unhealthy foods; and Factor 2, where the consumption of “Mediterranean diet” foods was prevalent. Factor 1 showed a direct relationship with BMI (β = 0.226; r2 = 0.259; p < 0.001), while the association with Factor 2 was inverse (β = −0.037; r2 = 0.230; p = 0.348). A total of four categories were defined (Prudent, Healthy, Western, and Compensatory) through classification of the sample in higher or lower adherence to each factor and combining the possibilities. Western and Compensatory dietary patterns, which were characterized by high-density foods consumption, showed positive associations with overweight prevalence. Further analysis showed that prevention of overweight must focus on limiting the intake of known deleterious foods rather than exclusively enhance healthy products.

Dopamine gene methylation patterns are associated with obesity markers and carbohydrate intake

“…The MENA cohort is constituted by previous clinical trials analyzing genome‐environmental interactions concerning weight management and associated metabolic outcomes (Abete et al., 2015; Huerta, Navas‐Carretero, Prieto‐Hontoria, Martínez, & Moreno‐Aliaga, 2015; Larsen et al., 2010; Martínez‐González et al., 2014; Petersen et al., 2006; San‐Cristobal et al., 2015; Santos et al., 2016; Zulet et al., 2011). Each study received ethical approval from appropriate local Human Research Ethics Committees.…”

Capturing health and eating status through a nutritional perception screening questionnaire (NPSQ9) in a randomised internet-based personalised nutrition intervention: the Food4Me study

“…Indeed, a previous study using the Spanish screening cohort of the Food4Me study has indicated that some of the items present in the questionnaires were related to specific dietary patterns [ 5 ]. In that study, significant ifferences were observed in the perceptions of healthy eating habits between participants who were characterized by “ Western ” and “ Compensatory ” dietary patterns compared to participants reporting “ Prudent ” and “ Healthy ” dietary patterns.…”

“…However, the perceived benefit of consuming certain foods is influenced by multiple individual factors, which may alter eating habits and dietary patterns. Identification of these factors and dietary patterns is an important challenge for the promotion of well-being and public health [ 4 , 5 ]. Identification of barriers to the consumption of healthy foods is imperative to the design of effective behaviour change interventions and policies [ 6 ].…”

“…Previous studies have indicated positive associations between perception of healthy food intake and diet quality [ 9 – 11 ]. A preceding study on dietary patterns in a Spanish cohort showed that participants who presented with “ prudent” or “healthy” dietary patterns reported greater proportions of positive perceptions of healthy eating than those who exhibited a “Western” or “compensatory” dietary patterns [ 5 ]. Similarly, the perception of healthy eating has been presented by some authors as a plausible predictor of behavioural intentions regarding food choices [ 12 ].…”

Lifestyle Patterns and Weight Status in Spanish Adults: The ANIBES Study

“…Data-driven methods explore the similarities between different food options in specific population groups [8]. Specifically, cluster analyses include several techniques aimed at grouping together individuals sharing a number of features or similar lifestyles.…”