the-psoriasis-treatment

In this previous post I analyzed some data from the China Study that included counties where there were cases of schistosomiasis infection. Following one of Denise Minger ’s suggestions, I removed all those counties from the data. I was left with 29 counties, a much smaller sample size. I then ran a multivariate analysis using WarpPLS ( warppls.com ), like in the previous post, but this time I used an algorithm that identifies nonlinear relationships between variables. Below is the model with the results. (Click on it to enlarge. Use the "CRTL" and "+" keys to zoom in, and CRTL" and "-" to zoom out.) As in the previous post, the arrows explore associations between variables. The variables are shown within ovals. The meaning of each variable is the following: aprotein = animal protein consumption; pprotein = plant protein consumption; cholest = total cholesterol; crcancer = colorectal cancer. What is total cholesterol doing at the right part of the gr...

Regardless of type of exercise, disease markers are generally associated with intensity of exertion over time. This association follows a J-curve pattern. Do too little of it, and you have more disease; do too much, and incidence of disease goes up. There is always an optimal point, for each type of exercise and marker. A J curve is actually a U curve, with a shortened left end. The reason for the shortened left end is that, when measurements are taken, usually more measures fall on the right side of the curve than on the left. The figure below (click to enlarge) shows a schematic representation that illustrates this type of relationship. (I am not very good at drawing.) Different individuals have different curves. If the vertical axis was a measure of health, as opposed to disease, then the curve would have the shape of an inverted J. The idea that long distance running causes heart disease has been around for a while. Is it correct? If it is, then one would expect to see certain thin...

The hypothesis that blood cholesterol levels are positively correlated with heart disease (the lipid hypothesis) dates back to Rudolph Virchow in the mid-1800s. One famous study that supported this hypothesis was Ancel Keys's Seven Countries Study, conducted between the 1950s and 1970s. This study eventually served as the foundation on which much of the advice that we receive today from doctors is based, even though several other studies have been published since that provide little support for the lipid hypothesis. The graph below (source: canibaisereis.com , with many thanks to O Primitivo) shows the results of one study, involving many more countries than Key's Seven Countries Study, that actually suggests a NEGATIVE linear correlation between total cholesterol and cardiovascular disease. Now, most relationships in nature are nonlinear, with quite a few following a pattern that looks like a U-curve (plain or inverted); sometimes called a J-curve pattern. The graph below (sou...