splitting up tables based on read/write frequency of columns

This is really a theoretical/anecdotal question, as I'm not at a scale yet where this would measurable. I want to investigate while this is fresh in my mind...

I recall reading that unless a row has columns that are TOASTed, an `UPDATE` is essentially an `INSERT + DELETE`, with the previous row marked for vacuuming.

A few of my tables have the following characteristics:
- The Primary Key has many other tables/columns that FKEY onto it.
- Many columns (30+) of small data size
- Most columns (90%) are 1 WRITE(UPDATE) for 1000 READS
- Some columns (10%) do a bit of internal bookkeeping and are 1 WRITE(UPDATE) for 50 READS

Has anyone done testing/benchmarking on potential efficiency/savings by consolidating the frequent UPDATE columns into their own table?