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Putative biases in estimating mortality attributable to obesity in the US population

International Journal of Obesity volume 31, pages 1449–1455 (2007)Cite this article

Abstract

Background:

A recent analysis concluded that there were fewer excess deaths attributable to obesity in the US population than previously believed. This analysis may not have fully corrected for two putative biases, the regression-dilution and the reverse-causation biases. It is not presently known whether correcting for these biases would increase estimates of excess deaths attributable to obesity.

Methods:

All-cause mortality hazard ratios (HRs) for different body mass index (BMI) categories were calculated and adjusted for confounding factors, using data from the prospective Atherosclerosis Risk in Communities Study. The analysis was based on 12 457 individuals aged 51–70 years and 606 all-cause deaths during a 5.3-year follow-up. The HRs were corrected for the regression-dilution and reverse-causation biases, and compared with data from a previously published study to evaluate the effects of correcting for these putative biases on estimates of excess deaths attributable to obesity in the US population.

Results:

The uncorrected all-cause mortality HR for obesity (BMI⩾30) was 1.26 (95% confidence interval (95% CI)=1.01–1.58), using the 21–25 kg/m2 as ideal-weight category. Correcting for regression dilution increased the HR to 1.46 (95% CI=1.17–1.83). Correcting for both putative biases increased it further to 2.70 (95% CI=1.31–5.57). Such increases in HRs are consonant with increases of several hundred percent in estimates of deaths attributable to obesity in the US.

Conclusions:

Correcting for putative biases yielded increases in all-cause mortality HRs for obesity that correspond to substantial increases in estimates of excess deaths attributable to obesity in the US population.

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Acknowledgements

The Atherosclerosis Risk in Communities Study (ARIC) is conducted and supported by the National Heart Lung and Blood Institute (NHLBI) in collaboration with the ARIC investigators. This manuscript was prepared using a limited access dataset obtained by the NHLBI and does not necessarily reflect the opinions or views of the ARIC or the NHLBI. This work is supported in part by NIH grant P30DK056336.

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Authors and Affiliations

  1. Department of Health and Nutrition Sciences, Brooklyn College of the City University of New York, Brooklyn, NY, USA

    J A Greenberg

  2. Division of Rheumatology, Johns Hopkins University, School of Medicine, Baltimore, MD, USA

    K Fontaine

  3. Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA

    D B Allison

Authors
  1. J A Greenberg
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  2. K Fontaine
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  3. D B Allison
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Correspondence to J A Greenberg.

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Greenberg, J., Fontaine, K. & Allison, D. Putative biases in estimating mortality attributable to obesity in the US population. Int J Obes 31, 1449–1455 (2007). https://doi.org/10.1038/sj.ijo.0803615

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