Sources and severity of bias in estimates of the BMI–mortality association

Ryan K. Masters

Population Studies, 2023, vol. 77, issue 1, 35-53

Abstract: Estimates of mortality differences by body mass index (BMI) are likely biased by: (1) confounding bias from heterogeneity in body shape; (2) positive survival bias in high-BMI samples due to recent weight gain; and (3) negative survival bias in low-BMI samples due to recent weight loss. I investigate these sources of bias in the National Health and Nutrition Examination Survey (NHANES) 1988–94 and 1999–2006 linked to mortality up to 2015 (17,784 cases; 4,468 deaths). I use Cox survival models to estimate BMI differences in all-cause mortality risks among adults aged [45–85) in the United States. I test for age-based differences in BMI–mortality associations and estimate functional forms of the association using nine BMI levels. Estimates of the BMI–mortality association in NHANES data are significantly affected by all three biases, and obesity–mortality associations adjusted for bias are substantively strong at all ages. The mortality consequences of overweight and obesity have likely been underestimated, especially at older ages.

Date: 2023
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DOI: 10.1080/00324728.2023.2168035

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Population Studies is currently edited by John Simons, Francesco Billari, James J. Brown, John Cleland, Andrew Foster, John McDonald, Tom Moultrie, Mikko Myrsklä, Alice Reid, Wendy Sigle-Rushton, Ronald Skeldon and Frans Willekens

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