# GLP-1 Weight Loss Across 32 Trials: The 9.36% Average and Its Spread | This GLP

A meta-regression of 32 trials and 40,408 participants found 9.36% mean weight reduction with I² of 99.6% — and what actually explained the spread between trials.

Publisher: This GLP Editorial Team
Canonical: https://thisglp.com/research/glp1-weight-loss-pooled-average
Updated: 2026-09-18
Published: 2026-09-16

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Evidence

# GLP-1 Weight Loss Across 32 Trials: The 9.36% Average and Its Spread

Thirty-two trials give a mean weight reduction of 9.36%. They also disagree with each other almost completely, which is the more useful number.

[This GLP Editorial Team](https://thisglp.com/about)September 20266 min readUpdated September 2026

Pooled across 32 trials, 40,408 participants · 9.36% · 7.92 · 10.80 · I² = 99.6% — the trials do not agree with each other · A tight interval around a mean that almost no trial reported

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## Key takeaways

-   A meta-regression pooled 32 trials covering 40,408 participants, searched to February 2026.
-   The weighted mean weight reduction was 9.36%, 95% CI 7.92% to 10.80%.
-   Heterogeneity between trials was I² = 99.6%, meaning the trials almost entirely disagree.
-   Trials with more baseline anxiety or depression reported larger weight loss — a study-level association, not a fact about individuals.
-   Trials in people with type 2 diabetes, sleep apnea or fatty liver disease reported smaller responses.

A single number for how much weight these drugs take off is the most requested figure in this market and the least reliable one. Here is a pooled estimate built from forty thousand people, and the statistic that tells you not to use it.

## The number, and the number beside it

Thirty-two trials, 40,408 participants, searched across four databases to February 2026. [\[1\]](https://thisglp.com/research/glp1-weight-loss-pooled-average#ref-1) The weighted mean weight reduction was 9.36%, with a 95% confidence interval from 7.92% to 10.80%. That looks precise.

The heterogeneity statistic was I² = 99.6%, p<0.001. I² estimates how much of the variation between trial results is real rather than chance. At 99.6%, essentially all of it is real. The trials are not noisy measurements of one underlying number — they are measurements of different numbers.

What a tight interval means when I² is that high

The confidence interval describes uncertainty about the average. It does not describe the spread of what happened. With this much heterogeneity, an individual trial could sit far outside 7.92% to 10.80% and be entirely consistent with the pooled result, and an individual person sits further out still. A narrow interval around a meaningless average is a familiar trap, and it is a cousin of [the same estimate answering two questions](https://thisglp.com/research/do-glp1-drugs-improve-blood-vessel-function).

## What explained the spread

Subgroup analysis found larger weight reduction with the dual GLP-1 and GIP agonist, tirzepatide, and with treatment lasting 72 weeks or more. Neither is surprising and both come from subgrouping rather than from a designed comparison, which makes them weaker than they look.

The meta-regression found something less expected. Baseline anxiety or depression was positively associated with weight-loss efficacy, β = 2.44, p<0.001, with study-level R² of 81.34%. Type 2 diabetes, obstructive sleep apnea and metabolic dysfunction-associated fatty liver disease were each negatively correlated with response, all at p<0.05; the abstract gives no coefficients for those, so none appear here.

This does not say anxious people lose more weight

Meta-regression works on trials, not people. The finding is that trials whose participants had more baseline anxiety or depression reported larger average weight loss. Concluding from that what will happen to any individual with anxiety is the ecological fallacy — the classic example being that a country’s average income predicts nothing reliable about the person next to you. Thirty-two data points also make an R² of 81% fragile. It is a hypothesis about why trials differ, not a trait that predicts your result.

## Why the negative correlations are more useful

Because they are consistent with what individual trials already show. Weight loss on these drugs is reliably smaller in people with type 2 diabetes than in people without it, which is why the landmark obesity and diabetes trials report different headline figures and are not interchangeable — [reading the right trial for your situation](https://thisglp.com/research/semaglutide-cochrane-review) matters more than the pooled average does.

Sleep apnea and fatty liver disease pointing the same way is a newer observation and carries the same study-level caveat. All three travel together with metabolic disease, so whether any one of them is doing something on its own is not answerable here.

## What to do with a number like 9.36%

Use it as a floor for what the class does, not as a forecast for what you will do. Any estimate a seller or a calculator produces — including [the one on this site](https://thisglp.com/tools/glp1-expected-weight-loss) — is drawn from trial averages and inherits this spread. It is an estimate, and this study is the clearest available measure of how wide the real distribution around it is.

The broader lesson is one this desk keeps arriving at from different directions: a pooled figure is a summary of a literature, not a description of a person, and the literature here is far less settled than the marketing suggests — the same distance [between one famous trial and everything behind it](https://thisglp.com/research/glp1-in-children-all-eighteen-trials).

## Frequently asked

How much weight will I lose?

No study can tell you. The pooled average across 32 trials was 9.36%, but heterogeneity between those trials was I² = 99.6%, meaning they were measuring genuinely different numbers rather than one number imprecisely.

Does anxiety or depression make the drug work better?

Nothing here shows that. The association is between trials — studies with more baseline anxiety or depression reported larger average weight loss — and applying a study-level pattern to an individual is the ecological fallacy.

Why did people with diabetes lose less?

The analysis reports the correlation and not its cause. Smaller weight loss in type 2 diabetes is a consistent finding across individual trials too, which is why obesity and diabetes trial results are not interchangeable.

Is a narrow confidence interval reassuring here?

Not in the way it looks. The interval describes uncertainty about the average, not the spread of individual results, which this analysis shows is very wide.

## Sources

1.  \[1\] Lu D, et al. (2026). Weight Reduction Heterogenicity and Mediators of GLP-1RAs and Dual Agonists for Individuals With Obesity: A Meta-Analysis Clinical Obesity. [PMID 42733128](https://pubmed.ncbi.nlm.nih.gov/42733128/)

## Where to get it

### Best GLP-1 injections

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