Comparing my trajectory with the trial curves, carefully — a second dataset

Comparing my trajectory with the trial curves, carefully — a second dataset — setting out what I have, and where I think it stops being reliable.

Maintenance rather than loss, which is the part of this that almost nobody writes about.

I have been at roughly the same weight for 15 months. The interesting questions are all different from the ones I had at the start, and the documentation here is much thinner on this phase.

I would like to compare notes with people who are further along, and I would like to know what the published evidence says about this phase specifically rather than by extrapolation.

Seasonal patterns: some people report weight loss is slower in winter than summer. Body composition and activity changes might contribute. Noting the season is useful context.

Exercise volume changes: increasing exercise intensity or duration can mask weight loss (muscle gain) on the scale. Noting exercise changes when reporting weight helps interpret results.

the opening post answers the question as asked. The question underneath it is different.

Plateaus and resets: if weight loss stalls and then resumes, that is ordinary. It is not evidence that the medication stopped working. It is not evidence that it is still working either. It is a data point in a longer record.

I read post #3 twice before replying, because I had assumed the opposite.

Non-scale victories: muscle gain or maintenance, clothing fit, energy level, and capability (like climbing stairs without breathlessness) are measurements that scale-based weight misses.

Rate of change: reporting progress as "lost 5 kg in 12 weeks" is more useful than "currently at 82 kg" because the rate tells you whether the change is steady, accelerating, or stalling.

Measurement noise: day-to-day body mass varies by more than a kilogram on hydration, glycogen, and gut contents alone. A weekly reading is a single noisy sample of a distribution. A seven-day rolling mean of daily readings has much lower noise.

Protein intake and resistance training: both self-reported and therefore optimistic in most reports. Recording them anyway creates a record you can look back on.

Medication changes: escalating dose, or adding or removing other medications, can affect the rate of weight loss. Documenting medication changes alongside weight makes the record interpretable.

Picking up post #7: that is the part I would want checked first.

Menstrual cycle: for people who menstruate, weight can shift by several pounds across the cycle due to fluid retention and other factors. Noting cycle phase when weighing reduces apparent noise.

Picking up post #8: that is the part I would want checked first.

Longitudinal report with the method stated: same scale, same time of day, same conditions. A scale is a tool; use the same one each time. Consistency matters more than accuracy at capturing absolute weight.

Coming back to post #10, because the follow-up matters more than the original answer.

Exercise volume changes: increasing exercise intensity or duration can mask weight loss (muscle gain) on the scale. Noting exercise changes when reporting weight helps interpret results.

Seasonal patterns: some people report weight loss is slower in winter than summer. Body composition and activity changes might contribute. Noting the season is useful context.

Medication changes: escalating dose, or adding or removing other medications, can affect the rate of weight loss. Documenting medication changes alongside weight makes the record interpretable.