Evidence map›Paper›PMID 27075676›Full record

ArticleEpidemiology (Cambridge, Mass.)2016

Collider Bias Is Only a Partial Explanation for the Obesity Paradox.

Matthew Sperrin, Jane Candlish, Ellena Badrick, Andrew Renehan, Iain Buchan

Abstract read
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Article in Epidemiology (Cambridge, Mass.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
78citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

78 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  17. Depicting patient-reported outcome measures within directed acyclic graphs: practice and implications for causal reasoning.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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18 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Matthew SperrinFrom the aHealth eResearch Centre, Farr Institute, and bInstitute of Cancer Sciences, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.
Jane Candlish
Ellena Badrick
Andrew Renehan
Iain Buchan

Funding

Medical Research Council MC_PC_13042Medical Research Council MR/K006665/1
6 · The paper itself

Abstract

background"Obesity paradox" refers to an association between obesity and reduced mortality (contrary to an expected increased mortality). A common explanation is collider stratification bias: unmeasured confounding induced by selection bias. Here, we test this supposition through a realistic generative model.

methodsWe quantify the collider stratification bias in a selected population using counterfactual causal analysis. We illustrate the bias for a range of scenarios, describing associations between exposure (obesity), outcome (mortality), mediator (in this example, diabetes) and an unmeasured confounder.

resultsCollider stratification leads to biased estimation of the causal effect of exposure on outcome. However, the bias is small relative to the causal relationships between the variables.

conclusionsCollider bias can be a partial explanation of the obesity paradox, but unlikely to be the main explanation for a reverse direction of an association to a true causal relationship. Alternative explanations of the obesity paradox should be explored. See Video Abstract at http://links.lww.com/EDE/B51.

Indexed as

Confounding Factors, EpidemiologicMortalityBiasHumansLogistic ModelsObesity

Identifiers

PMID27075676
PMCPMC4890843

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.