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Article CommentaryCommentary
Open Access

Addressing Reverse Causation Bias in the Obesity Paradox Is Not “One Size Fits All”

Deirdre K. Tobias
DOI: 10.2337/dci17-0010 Published 1 August 2017
Deirdre K. Tobias
Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
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  • For correspondence: dtobias@bwh.harvard.edu

The obesity epidemic is a global crisis, extending well beyond the U.S. and Western countries. Korea is no exception, with the prevalence of overweight/obesity (BMI ≥23 kg/m2) escalating in recent decades to 61.3% for men and 45.3% for women in 2014 (1).

Despite the overwhelming evidence implicating excess adiposity in the development of several chronic diseases, there has been a prolonged debate surrounding the association between BMI and all-cause mortality. The public health implications of this relationship are not trivial and contribute to the ongoing attention given to this topic.

In this issue of Diabetes Care, Lee et al. (2) report their analysis of 12.8 million adults aged 18–99 years in the National Health Insurance Service of Korea at baseline examinations in 2001, with follow-up through 2013. BMI was evaluated in relation to all-cause mortality, demonstrating a U-shaped association between BMI and all-cause mortality. The authors concluded that the optimal BMI for survival after 10.5 years was 25.0–30.9 kg/m2 for men and 23.5–29.4 kg/m2 for women; thus, maintaining a body weight in the range of overweight and obesity appears ideal for longevity. This controversial finding has been observed by many, but not all, prior studies of BMI and mortality in those with and without diabetes. Novel to this publication by Lee et al. (2) is the additional observation that the optimal BMI increases with worsening state of glycemia.

The methodological challenges in quantifying the association between body weight and mortality are complex and have been exhaustively described in detail elsewhere (3). Reverse causation emerges as a prevailing explanation of the bias underlying the paradoxical association, although other potential biases likely coexist (4). This broad term includes confounding by antecedent weight loss or other determinants of low body weight (e.g., chronic illness, malnutrition, infectious disease, smoking duration and intensity) that in turn elevate mortality risk.

Sources of reverse causation bias depend on patterns of cultural and lifestyle factors, prevailing infectious and chronic illnesses, variability in socioeconomic status, and many other factors. I commend Lee et al. (2) for conducting extensive sensitivity analyses to address potential sources of reverse causation bias that have been identified in other previous populations. However, it is not surprising that exclusions for smoking status and baseline cancer, heart disease, or stroke had minimal effect on altering the paradoxical U-shaped association in their analysis, given these factors were not positively associated with low BMI in the Korean population (Supplementary Table 2 in Lee et al. [2]). It is likely that other characteristics were more pertinent confounders in this study population.

Lack of information on cause-specific mortality is another major limitation in the interpretation of these findings. In an analysis of 220,000 Chinese men with 15 years of follow-up, Chen et al. (5) observed that an inverse relationship between BMI and mortality persisted for deaths due to respiratory diseases and cancers of the lung and stomach. However, overweight and obesity were positively related to deaths from vascular diseases and diabetes or renal causes. Similarly, an analysis of nearly 11 million adults worldwide illustrated that the elevated mortality at lower BMIs predominantly included deaths from respiratory causes (6). In Korea, respiratory deaths due to pneumonia have risen alarmingly to the fifth leading cause of death in 2014, and deaths from chronic lower respiratory disease rank ninth (7). Malignancies have remained the leading cause of death for both men and women in Korea for more than a decade, and cancers of the lung, liver, and stomach rank the highest. Collectively, these trends support the high potential for confounding in this analysis by Lee et al. (2) by unmeasured infectious and chronic diseases at baseline, as well as lifestyle and socioeconomic factors, which might have been elucidated with information on cause-specific mortality. Further, by evaluating only all-cause mortality, this analysis obscures important relationships between BMI and cardiovascular mortality and thus masks critical areas of opportunity for prevention.

Attributing a survival advantage to excess body weight in the absence of biological evidence is misleading and potentially hazardous. The authors, as have others before them, propose that accumulating excess adipose tissue may causally benefit mortality risk by acting as a “metabolic reservoir” of fat, protecting other tissues from overexposure. Evidence now overwhelmingly indicates that adipose tissue is not simply a benign storage area for excess calories but rather a metabolically active endocrine organ (8). Adipocytes become dysfunctional when enlarged, and the cascade of hormonal and cardiometabolic consequences that follows is likely what implicates excess adiposity as an established risk factor of so many health outcomes.

Patient body weight and mortality are two readily available statistics in increasingly larger health records databases; therefore, analyses of this relationship will no doubt continue to be published. The effectiveness of various methodological approaches to address sources of bias will differ widely based on populations’ underlying health status, determinants and distribution of major confounding factors, and prevalence of competing risk factors across BMI strata. Analyzing individuals’ historical highest body weight to address unintentional weight loss from illness and aging may provide another solution (9). In most cases, the paradoxical association between BMI and mortality is resolved with these strategies (6), including among subjects with type 2 diabetes (10), demonstrating a positive dose-response, with elevated body weight incurring a higher mortality risk. Overall advice should remain to maintain a healthy body weight for the prevention and management of related chronic diseases, including type 2 diabetes.

Article Information

Funding. D.K.T. is supported by National Institutes of Health National Institute of Diabetes and Digestive and Kidney Diseases grant K01DK103720-01.

Duality of Interest. No potential conflicts of interest relevant to this article were reported.

Footnotes

  • See accompanying article, p. 1026.

  • © 2017 by the American Diabetes Association.
http://www.diabetesjournals.org/content/license

Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals.org/content/license.

References

  1. Shin HY, Kang HT. Recent trends in the prevalence of underweight, overweight, and obesity in Korean adults: the Korean National Health and Nutrition Examination Survey from 1998 to 2014. J Epidemiol. 15 April 2017 [Epub ahead of print]. https://doi.org/10.1016/j.je.2016.08.014
  2. Lee, EY, Lee Y-h, Yi S-W, Shin S-A, Yi J-J. BMI and all-cause mortality in normoglycemia, impaired fasting glucose, newly diagnosed diabetes, and prevalent diabetes: a cohort study. Diabetes Care 2017;40:1026–1033pmid:24078231
    1. Tobias DK,
    2. Hu FB
    . Does being overweight really reduce mortality? Obesity (Silver Spring) 2013;21:1746–1749pmid:24078231
    1. Robinson WR,
    2. Furberg H,
    3. Banack HR
    . Selection bias: a missing factor in the obesity paradox debate. Obesity (Silver Spring) 2014;22:625pmid:24738156
    1. Chen Z,
    2. Yang G,
    3. Offer A, et al
    . Body mass index and mortality in China: a 15-year prospective study of 220 000 men. Int J Epidemiol 2012;41:472–481pmid:22296991
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    2. Bhupathiraju ShN,
    3. Wormser D, et al.; Global BMI Mortality Collaboration
    . Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet 2016;388:776–786pmid:27423262
    1. Shin HY,
    2. Lee JY,
    3. Song J, et al
    . Cause-of-death statistics in the Republic of Korea, 2014. J Korean Med Assoc 2016;59:221–232
    1. Fontana L,
    2. Hu FB
    . Optimal body weight for health and longevity: bridging basic, clinical, and population research. Aging Cell 2014;13:391–400pmid:24628815
    1. Yu E,
    2. Ley SH,
    3. Manson JE, et al
    . Weight history and all-cause and cause-specific mortality in three prospective cohort studies. Ann Intern Med 2017;166:613–620pmid:28384755
    1. Tobias DK,
    2. Pan A,
    3. Jackson CL, et al
    . Body-mass index and mortality among adults with incident type 2 diabetes. N Engl J Med 2014;370:233–244pmid:24428469

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