Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses.

Excess significance bias We did a test for excess significance to determine whether the number of studies with nominally significant results (P<0.05) was higher than expected, based on statistical power. 32 Small study effects We used Egger's regression asymmetry test to detect potential small study effects, whereby smaller studies sometimes show different, often larger, effect estimates than large studies. 33 Largest study significance We assessed whether effect estimates from the largest original research article (that is, the study with the highest participant count) included in the pooled analyses had a P value below 0.05.

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