Investigation of bias due to selective inclusion of study effect estimates in meta-analyses of nutrition research.
Res Synth Methods
; 15(4): 524-542, 2024 Jul.
Article
in En
| MEDLINE
| ID: mdl-38316613
ABSTRACT
We aimed to explore, in a sample of systematic reviews (SRs) with meta-analyses of the association between food/diet and health-related outcomes, whether systematic reviewers selectively included study effect estimates in meta-analyses when multiple effect estimates were available. We randomly selected SRs of food/diet and health-related outcomes published between January 2018 and June 2019. We selected the first presented meta-analysis in each review (index meta-analysis), and extracted from study reports all study effect estimates that were eligible for inclusion in the meta-analysis. We calculated the Potential Bias Index (PBI) to quantify and test for evidence of selective inclusion. The PBI ranges from 0 to 1; values above or below 0.5 suggest selective inclusion of effect estimates more or less favourable to the intervention, respectively. We also compared the index meta-analytic estimate to the median of a randomly constructed distribution of meta-analytic estimates (i.e., the estimate expected when there is no selective inclusion). Thirty-nine SRs with 312 studies were included. The estimated PBI was 0.49 (95% CI 0.42-0.55), suggesting that the selection of study effect estimates from those reported was consistent with a process of random selection. In addition, the index meta-analytic effect estimates were similar, on average, to what we would expect to see in meta-analyses generated when there was no selective inclusion. Despite this, we recommend that systematic reviewers report the methods used to select effect estimates to include in meta-analyses, which can help readers understand the risk of selective inclusion bias in the SRs.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Research Design
/
Bias
/
Meta-Analysis as Topic
/
Diet
/
Systematic Reviews as Topic
Limits:
Humans
Language:
En
Journal:
Res Synth Methods
Year:
2024
Type:
Article
Affiliation country:
Australia