[2026 update] People with a low starting BMI: where the evidence stops

People with a low starting BMI: where the evidence stops Writing it up because I had to work it out twice and would rather nobody else did.

Asking about a population rather than about a person.

The published trials in this class mostly enrolled a fairly specific group, and the questions here frequently come from people well outside it. I would like to understand what the honest position is when someone falls outside the studied population: not "it is fine" and not "there is no data", but what the reasoning actually looks like.

Extrapolating a point estimate to somebody well outside the enrolled range should be described as an extrapolation every time it is done.

Worth separating two things that the opening post runs together.

Post-surgical populations, particularly after procedures affecting the gastrointestinal tract, interact with a delayed-emptying mechanism in ways that need specialist input.

That is where I would start, not where I would stop.

Athletes and people in substantial training loads are effectively unstudied, and the questions asked here about performance have no trial evidence behind them at all.

This is the version I would want a new member to read first.

Older adults: sarcopenia risk is higher, polypharmacy is common, and the clinical trials did not enroll many people over 75. Extrapolating to very old people is extrapolating beyond the data.

I would treat the number as indicative rather than as a measurement.

Adolescents: a distinct evidence base exists. The compounds are not approved for routine adolescent obesity but are being studied. Adolescent physiology and psychology differ from adults' in ways that matter for this medication class.

On post #5 — agreed on the reasoning, with one qualification.

Dedicated trials in under-studied populations are the only real remedy and several are ongoing, which is worth saying rather than speculating.

A qualification I should have led with rather than closed on.

Picking up post #5: that is the part I would want checked first.

The most useful contribution here is usually a citation to whichever published document comes closest, with a plain statement of how far it is from the question.

The rule of thumb is fine; the edge cases are where it earns its keep.

Answering the question post #5 raises rather than the one it answers.

Genetic and ancestry-related differences in response are asked about regularly and the published evidence is thin enough that the honest answer is short.

Not the whole picture, but the part of it I can speak to.

The absence of a reported signal in a population that was barely enrolled is not evidence about that population.

That matches what I was told, which is not the same as knowing it.

Where a population is under-studied, registry data accumulates first and is confounded by indication in ways that are hard to correct.

Adding a source would improve this post and I do not have one to hand.

This is the first time the answer has come with its own limits attached. Appreciated.

The arithmetic in post #10 is right; the assumption feeding it is the part to check.

Being outside the studied population does not mean a treatment is unsafe. It means the usual evidence is not available and the reasoning has to be explicit.

Answering the question post #13 raises rather than the one it answers.

People on multiple medicines are under-represented in trials by design, and that is the population most of the interaction questions come from.

Not disagreeing with anyone above, just adding the bit I keep having to look up.