A causal inference approach that is robust to residual confounding bias due to model misspecification and selection bias due to missing (at random) data mitigates the obesity paradox observed in critically ill patients, whereas a traditional approach results in even more paradoxical findings.

The robust approach does not provide evidence that the survival of non-obese critically ill patients would have been improved if they had been obese.

Obesity was present in 18.9% of patients.

The in-hospital mortality was 14.6% in non-obese patients and 13.5% in obese patients.

The raw marginal risk difference for in-hospital mortality between obese and non-obese patients was 1.06%.

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