They kind of skipped a step. What you would do is then look at what the first principle axis is. In this particular case, it would be a 17-D vector, each element corresponding a food type. You would then look at which elements (food types) have the greatest magnitude.
In a toy example, imagine we had a 5D case where we have beer, cereal, fruit, beef, chicken, and salad, and we found out that the first principle axis is {0.3, 0.1, -0.5, 0.0. 0.2} (in the same order). Then the cause of the change would be due to primarily fruit and beer consumption.
I was looking for the same information. The article has a link to pdf with a more deep discussion of this case, and the explanation and the values of the weight of each product. http://people.maths.ox.ac.uk/richardsonm/SignalProcPCA.pdf
From the figure 4, after rescaling and rounding the coefficients
In a toy example, imagine we had a 5D case where we have beer, cereal, fruit, beef, chicken, and salad, and we found out that the first principle axis is {0.3, 0.1, -0.5, 0.0. 0.2} (in the same order). Then the cause of the change would be due to primarily fruit and beer consumption.