Performance of iteration through Words collection degrades as collection gets bigger

I was using a Do While loop using an index into Words. However, I have since tried other methods and found that a For Each to iterate the collection works incredibly much faster. I am still trying to determine if I can do what I want to do that way.

In the course of the processing I am replacing a single word with a phrase. In this case, using For Each, the cursor continues with the first word I used to replace, rather than continuing with the next word after the one I replaced. I am not sure how to mitigate that. For example:

Scanning this sentence:

Here is a BUA. We do not know what it means.

It scans BUA, then replace it so the line now reads

Here is a Big Undefined Acronym (BUA). We do not know what it means.

In this case, I want the next word scanned to be "We". However, it is "Big".

Here is a simplified version of the code:

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The For Each works as a workaround to the performance issue. To deal with the cursor location I added a JumpOver variable to count how many words I inserted so the next JumpOver passes through the loop it skips processing.

I'm still wondering why performance of For Each is so superior to using an index, and also why the performance using an index gets worse and worse as the document size increases.

Thanks for you interest!

My original loop was something like this

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I started out with this because I occasionally needed to look back or look ahead. I was not aware of the Next/Previous methods. Once I restructured with For Each and started using Next/Previous the thing runs like lightning.

Any idea why For Each is the fastest way to iterate a collection? I have a computer science/software development background but have no idea how that structure is implemented and why that would be faster.