Published in:
Open Access
01-12-2014 | Research
Using maximum weight to redefine body mass index categories in studies of the mortality risks of obesity
Author:
Andrew Stokes
Published in:
Population Health Metrics
|
Issue 1/2014
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Abstract
Background
The high prevalence of disease and associated weight loss at older ages limits the validity of prospective cohort studies examining the association between body mass index (BMI) and mortality.
Methods
I examined mortality associated with excess weight using maximum BMI—a measure that is robust to confounding by illness-induced weight loss. Analyses were carried out on US never-smoking adults ages 50-84 using data from the National Health and Nutrition Examination Surveys (1988-1994 and 1999-2004) linked to the National Death Index through 2006. Cox models were used to estimate hazard ratios for mortality according to BMI at time of survey and at maximum.
Results
Using maximum BMI, hazard ratios for overweight (BMI, 25.0-29.9 kg/m2), obese class 1 (BMI, 30.0-34.9 kg/m2) and obese class 2 (BMI, 35.0 kg/m2 and above) relative to normal weight (BMI, 18.5-24.9 kg/m2) were 1.28 (95% confidence interval [CI], 0.89-1.84), 1.67 (95% CI, 1.15-2.40), and 2.15 (95% CI, 1.47-3.14), respectively. The corresponding hazard ratios using BMI at time of survey were 0.98 (95% CI, 0.77-1.24), 1.18 (95% CI, 0.91-1.54), and 1.31 (95% CI, 0.95-1.81). The percentage of mortality attributable to overweight and obesity among never-smoking adults ages 50-84 was 33% when assessed using maximum BMI. The comparable figure obtained using BMI at time of survey was substantially smaller at 5%. The discrepancy in estimates is explained by the fact that when using BMI at time of survey, the normal category combines low-risk stable-weight individuals with high-risk individuals that have experienced weight loss. In contrast, only the low-risk stable-weight group is categorized as normal weight using maximum BMI.
Conclusions
Use of maximum BMI reveals that estimates based on BMI at the time of survey may substantially underestimate the mortality burden associated with excess weight in the US.