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

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.

Keywords:

• obesity
• overweight
• body mass index
• reverse causation
• principal component analysis
• survival analysis
• mortality
• NHANES
• population attributable fraction

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1 Ryan K. Masters is based in the Department of Sociology, University of Colorado Boulder, and also the University of Colorado Population Center.

2 Please direct all correspondence to Ryan K. Masters, Institute of Behavioural Science, University of Colorado Boulder, 483 UCB, Boulder, CO 80309-0483; or by E-mail: [email protected].

3 Funding for this study comes from the US Department of Health and Human Services, National Institutes of Health: (1) Eunice Kennedy Shriver National Institute of Child Health and Human Development, grant number P2C HD066613; and (2) National Institute on Aging, grant number R24AG045061.