Statistical Considerations: The investigators will utilize the intention-to-treat method. In the design and data collection testing of drugs as the template have been made (randomization, placebo, blinding, no attrition, no differential measuring errors, correct analysis); for the deviations from the perfect situation the investigators use epidemiological theory for guiding the analyses and interpreting the results. Preliminary analyses, based on means, medians, standard deviations and interquantile range will be provided to properly describe the outcomes of interest and stratification will be performed to assess the performance of the randomization of the assigned diet. Box-plots will therefore be produced to graphically evaluate the temporal trends in the response. The distribution of the outcomes will be studied and appropriate transformations will be applied, if needed, to improve symmetry and normality. Due to the longitudinal structure of the data, correlation among observations will be incorporated and linear mixed effects models will be carried out to study if (i) there is a temporal trend (ii) if the linear trend differs between treated and untreated individuals (iii) if the treatment effect between the intervention group and the control group is modified according to ERß genotypes, both for the common and the variant. A key step in analysis of longitudinal data is to identify the appropriate covariance structure that describes the correlations among the data points: independent covariance (no correlation), exchangeable covariance (equal correlation) or autoregressive covariance with correlation between responses decreasing with time between measurements. The investigators will identify the most appropriate structure, verified empirically with help of an information theoretic approach. Both statistical tests and confidence intervals will be produced to assess the significance of the effects, partial F test procedures will therefore be used to study the joined effect of main and interaction variables and appropriate statistical methods will be applied to study model fitting.