Publications by authors named "R Foraita"
Article Synopsis
- The study examines how traditional dietary assessments may fall short in accurately measuring children's intake of sweet and fatty snacks, which can contribute to obesity and health issues in childhood.
- Researchers analyzed urine samples from children in two different cohorts to identify metabolite biomarkers that correlate with the consumption of snacks like chocolate, candy, and ice cream.
- A total of 66 metabolites were linked to snack consumption, with associations found for specific types of snacks; however, many metabolites could not be specifically identified.
Introduction: Pharmacovigilance is vital for drug safety. The process typically involves two key steps: initial signal generation from spontaneous reporting systems (SRSs) and subsequent expert review to assess the signals' (potential) causality and decide on the appropriate action.
Methods: We propose a novel discovery and verification approach to pharmacovigilance based on electronic healthcare data.
Article Synopsis
- The study explored how vitamin D levels affect inflammation markers in children and teens across eight European countries.
- Researchers found that higher vitamin D levels were linked to increased levels of adiponectin and reduced inflammation scores, particularly in children with normal weight.
- In overweight or obese children, only a positive connection to one marker (IP-10) was seen, highlighting the need for weight management to see improvements in inflammation related to vitamin D.
Motivation: The Peter Clark (PC) algorithm is a popular causal discovery method to learn causal graphs in a data-driven way. Until recently, existing PC algorithm implementations in R had important limitations regarding missing values, temporal structure or mixed measurement scales (categorical/continuous), which are all common features of cohort data. The new R packages presented here, micd and tpc, fill these gaps.
View Article and Find Full Text PDFChildhood obesity is a complex disorder that appears to be influenced by an interacting system of many factors. Taking this complexity into account, we aim to investigate the causal structure underlying childhood obesity. Our focus is on identifying potential early, direct or indirect, causes of obesity which may be promising targets for prevention strategies.
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