It’s hard to find any real science to explore the various anecdotal ideas about what weight loss actually is, but here are two papers in full text form that I can study a bit more (they’re a bit impenetrable on quick reading). It’s not clear, however, that these are actually based very much on experiment and measurement.
The graphs in these papers might be useful for future predictions.
My quick take on this is that different food consumption (than my baseline restriction diet) could either alter electrolyte balance or increase glycogen (like high carbs might “reload” my lost glycogen quickly) and glycogen then has high water absorption and thus so-called “water weight”.
But big swings in daily continue to show, as seen below (need a few more days to get better pattern, it’s a pain to have so much elapsed time involved in collecting data):
So today (x=20.14) was another discontinuous drop from Sunday reading (which had been a discontinuous rise since Saturday). But this also demonstrates how anomalous Saturday was. So it’s anyone’s guess about tomorrow.
What is clear is that I have to stop letting this high-frequency fluctuation stop spooking me. But it’s also clear that my measured Sunday (my standard weekly weigh-in was misleading, yet again and that the trendline value would have been more “correct”).
So what I think was I was lucky (or perhaps unlucky) not to have encountered this before. My once-a-week weigh-ins were working fine (steady trendline) until they didn’t. Now perhaps what was happening all along was some of this day-to-day variability and thus it was just random that I never saw an anomalous Sunday point in the first 18 weeks and now have seen two-in-a-row. That can just happen by chance and thus I was deluded, before, in believing the steady trend I was seeing was what I should have expected.
So, in reality, daily weigh-ins, with then some data smoothing, is probably more useful than I first believed. It also fits the motivational ideas since a bad once-a-week weigh-in is seriously depressing over a long interval, whereas once you get used to the big variability in daily values a single “bad” value isn’t as discouraging as a bad weekly value.