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Big data

CONTRIBUTED BY SILVIA GAMUNDI

In 1966 the Statistics Department of North Carolina State University started a research project funded by the National Institute of Health to analyze agricultural data for improving crop yields. They studied variables such as temperature, grain type or fertilizer variety in order to identify patterns that turned out into better harvests. This is one of the stories commonly used to go back to the origins of Big Data, and also the birth of SAS ...

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Cochrane meta-anaylisis about Diet & Cardiovascular Disease

A meta-analysis is a statistical method in which results of individual studies are mathematically combined in order to improve the reliability of the results. This technique presents enormous advantages over classical literature reviews. Meta-analyses also present weaknesses and they are fundamentally limited by the quality of the underlying studies. The Cochrane Collaboration is an international network that, using the meta-analysis method, analyzes randomized clinical trials (RCT) available on various subjects, and synthesizes them into regularly updated systematic reviews. ...More...

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Estimation of Risk for Child or Adolescent Obesity at Birth

By analyzing data from 4,000 children born in Finland in 1986, researchers created a formula that accurately predicts the likelihood of a baby developing obesity during childhood. Importantly, the predictive accuracy of the models did not decline from childhood to adolescence, suggesting that the association between the traditional risk factors and obesity is stable until early adulthood. When the performance of genetics in predicting early obesity phenotypes was explored, with the largest list of obesity-SNPs ever used, it showed only a ...More...

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Is the Obesity Paradox an actual paradox ?

Being a paradox an anomaly, and inconsistency, it would be supposed to occur in very rare occasions. I am, however, amazed how often this so-called paradox manifests itself. This phenomenon was described quite a few years ago (1). Yet, the term “obesity paradox” was coined by Gruberg (2)  who found that patients with known coronary artery disease and BMI within the normal range (<25 kg/m2) who undergo percutaneous coronary intervention are at the highest risk for in-hospital complications and for increased ...More...

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