"Wuzzy" <[EMAIL PROTECTED]> wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
> Rich Ulrich <[EMAIL PROTECTED]> wrote in message
>
> Thanks Rich, most informative, I am trying to determine a method of
> comparing apples to oranges - it seems an improtant thing to try to
> do, perhaps it is impossible .
>
> I am trying to
> determine which is better, glycemic index or carbohydrate total in
> predicting glycemic load (Glycemic load=glycemic index*carbohydrate).
>
> my results as a matrix:
>
> GI load GI Carb
> GI load 1.000
> GI .533 1.000
> Carb .858 .124 1.000
>
> So it seems that carb affects GI load more than does GI.. but this is
> on ALL foods.. (nobody eats ALL foods so cannot extrapolate to human
> diet) but I don't think you're allowed to do this kind of comparison
> as Carb and GI aretotal different values:
>
> I suspected that you would be allowed to make the comparisons if you
> use Betas, ie. measure how many standard deviationGlycemic load=glycemic
index*carbohydrate
> changes of GI and Carb it requires.. If it takes a bigger standard
> deviation of Carb then you could say that it is more likely that carb
> has a bigger effect on glycemic load.
>
> you seem to suggest that even using standard deviation changes, you
> cannot compare apples to oranges. Which sounds right but is
> dissapointing..
The glycaemic index is calculated as the area under the blood
glucose curve for the two hours (or 3 hours for diabetics) after ingesting
enough of a food to include 50 grams of carbohydrate, divided by the same
area after ingesting 50 grams of pure glucose, expressed as a percentage.
In some cases a reference food other than glucose is used.
If the area under the curve is the glycaemic load you are studying I
would expect the model
Glycemic load=glycemic index*carbohydrate
to fit the data very well when the carbohydrate content is near 50 gm,
providing all the glycaemic indices have been calculated on the same basis.
Using correlations or beta coefficients as you are doing is appropriate
when linear relationships are involved, but not to test for goodness of fit
to this model.
What would be of interest would be a plot of the difference between
the predicted glycaemic load and the observed value,against carbohydrate,
especially for carbohydrate values far from 50 gm. If I have a meal of
mainly of eggs or meat, the total carbohydrate content is very low, so the
glycaemic load calculated from the formula may be wrong.
One difficulty with the whole Glycaemic Index approach is that there
is not, as far as I know, any way of calculating the glycaemic load from
foods like cheese,eggs and meat. If the body needs glucose, it will be made
from fat and protein foods.
It is not surprising that it could be hard to persuade volunteers to
ingest 8500 grams of processed cheese, containing 50gm of carbohydrate, in
order to determine its glycaemic index :-)
I would like to see another index constructed giving the glycaemic load
produced by 100 gm of each food, rather than the load produced by that
amount of food which contains 50gm of carbohydrate.
=================================================================
Instructions for joining and leaving this list, remarks about the
problem of INAPPROPRIATE MESSAGES, and archives are available at
http://jse.stat.ncsu.edu/
=================================================================
