Raj Padwal, MD, MSc; William D. Leslie, MD, MSc; Lisa M. Lix, PhD; Sumit R. Majumdar, MD, MPH
Note: This article has been reviewed and approved by the members of the Manitoba Bone Density Program Committee.
Disclaimer: The results and conclusions are those of the authors, and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, or other data providers is intended or should be inferred.
Acknowledgment: The authors thank the Manitoba Centre for Health Policy for the use of data contained in the Population Health Research Data Repository (Health Information Privacy Committee project number 2011/2012-31). The authors also thank Dr. Shuman Yang for assisting with R programming and figure preparation. Dr. Majumdar holds the Endowed Chair in Patient Health Management from the Faculties of Medicine and Dentistry and Pharmacy and Pharmaceutical Sciences, University of Alberta. Dr. Lix is supported by a Manitoba Research Chair from Research Manitoba.
Disclosures: Dr. Leslie reports grants from Genzyme and Amgen and speaker fees from Amgen, Eli Lilly, and Novartis outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M15-1181.
Editors' Disclosures: Christine Laine, MD, MPH, Editor in Chief, reports that she has no financial relationships or interests to disclose. Darren B. Taichman, MD, PhD, Executive Deputy Editor, reports that he has no financial relationships or interests to disclose. Cynthia D. Mulrow, MD, MSc, Senior Deputy Editor, reports that she has no relationships or interests to disclose. Deborah Cotton, MD, MPH, Deputy Editor, reports that she has no financial relationships or interest to disclose. Jaya K. Rao, MD, MHS, Deputy Editor, reports that she has stock holdings/options in Eli Lilly and Pfizer. Sankey V. Williams, MD, Deputy Editor, reports that he has no financial relationships or interests to disclose. Catharine B. Stack, PhD, MS, Deputy Editor for Statistics, reports that she has stock holdings in Pfizer.
Reproducible Research Statement:Study protocol, statistical code, and data set: Not available.
Requests for Single Reprints: William D. Leslie, MD, Department of Medicine (C5121), University of Manitoba, 409 Tache Avenue, Winnipeg, Manitoba R2H 2A6, Canada; e-mail, email@example.com.
Current Author Addresses: Drs. Padwal and Majumdar: General Internal Medicine, University of Alberta, 5-134 Clinical Sciences Building, 8440 112th Street, Edmonton, Alberta T6G 2G3, Canada.
Dr. Leslie: Department of Medicine (C5121), University of Manitoba, 409 Tache Avenue, Winnipeg, Manitoba R2H 2A6, Canada.
Dr. Lix: Department of Community Health Sciences, University of Manitoba, S113-750 Bannatyne Avenue, Winnipeg, Manitoba R3P 2H5, Canada.
Author Contributions: Conception and design: R. Padwal, W.D. Leslie, S.R. Majumdar.
Analysis and interpretation of the data: R. Padwal, W.D. Leslie, L.M. Lix, S.R. Majumdar.
Drafting of the article: R. Padwal, W.D. Leslie.
Critical revision of the article for important intellectual content: R. Padwal, W.D. Leslie, L.M. Lix, S.R. Majumdar.
Final approval of the article: R. Padwal, W.D. Leslie, L.M. Lix, S.R. Majumdar.
Provision of study materials or patients: W.D. Leslie.
Statistical expertise: W.D. Leslie, L.M. Lix.
Administrative, technical, or logistic support: W.D. Leslie.
Collection and assembly of data: W.D. Leslie.
Prior mortality studies have concluded that elevated body mass index (BMI) may improve survival. These studies were limited because they did not measure adiposity directly.
To examine associations of BMI and body fat percentage (separately and together) with mortality.
Adults aged 40 years or older referred for bone mineral density (BMD) testing.
Participants had dual-energy x-ray absorptiometry (DXA), entered a clinical BMD registry, and were followed using linked administrative databases. Adjusted, sex-stratified Cox models were constructed. Body mass index and DXA-derived body fat percentage were divided into quintiles, with quintile 1 as the lowest, quintile 5 as the highest, and quintile 3 as the reference.
The final cohort included 49 476 women (mean age, 63.5 years; mean BMI, 27.0 kg/m2; mean body fat, 32.1%) and 4944 men (mean age, 65.5 years; mean BMI, 27.4 kg/m2; mean body fat, 29.5%). Death occurred in 4965 women over a median of 6.7 years and 984 men over a median of 4.5 years. In fully adjusted mortality models containing both BMI and body fat percentage, low BMI (hazard ratio [HR], 1.44 [95% CI, 1.30 to 1.59] for quintile 1 and 1.12 [CI, 1.02 to 1.23] for quintile 2) and high body fat percentage (HR, 1.19 [CI, 1.08 to 1.32] for quintile 5) were associated with higher mortality in women. In men, low BMI (HR, 1.45 [CI, 1.17 to 1.79] for quintile 1) and high body fat percentage (HR, 1.59 [CI, 1.28 to 1.96] for quintile 5) were associated with increased mortality.
All participants were referred for BMD testing, which may limit generalizability. Serial measures of BMD and weight were not used. Some measures, such as physical activity and smoking, were unavailable.
Low BMI and high body fat percentage are independently associated with increased mortality. These findings may help explain the counterintuitive relationship between BMI and mortality.
A lower mortality rate among overweight and mildly to moderately obese adults (the “obesity paradox”) is unexplained. Studies documenting this paradox are limited because body mass index (BMI) is an imperfect and indirect measure of adiposity.
In this population-based cohort study of middle-aged and older adults referred for bone mineral density testing, low BMI and high body fat percentage were independently associated with increased all-cause mortality among men and women.
Body fat percentage and BMI were measured only once at baseline.
The independent relationship between increased body fat percentage and mortality may help explain the obesity paradox.
Table 1. Baseline Demographic Characteristics, Deaths, and Death Rates*
Scatter plot of quintiles of body fat percentage, by BMI.
Gray vertical and horizontal lines indicate the quintiles of body fat and BMI, respectively. BMI = body mass index.
Appendix Table 1. Cohort Mortality Rates Compared With National and Provincial Mortality Rates*
Hazard ratios for death in age-adjusted and fully adjusted models that included BMI and body fat percentage separately.
Reference median values for BMI and mean body fat were 26 kg/m2 and 32% for women and 27 kg/m2 and 30% for men. BMI = body mass index.
Table 2. Associations of BMI and Body Fat Percentage (Separately) With Mortality
Hazard ratios for death in age-adjusted and fully adjusted models that included BMI and body fat percentage together.
Table 3. Associations of BMI and Body Fat Percentage (Together) With Mortality
Appendix Table 2. Sensitivity Analysis Using World Health Organization Thresholds for BMI
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Investigator, Dr. William Leslie, explains why body composition may be a more important predictor of health than BMI.
Dong Hoon Lee, MD
Kaiser Permanente, Redwood City Medical Center, CA 94063
May 3, 2016
Relationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality: A Cohort Study (re-submitting after edition)
TO THE EDITOR: Padwal and Leslie’s analysis among fat percentage, BMI, and all-cause mortality was very interesting in terms of addressing the area of uncertainty with the traditionally used anthropometric measurements that is represented by BMI (body Mass Index). This study must be robust given its large population and many years of the cohort, and there wouldn’t be a much better study design to examine the question being sought in this study though it was performed retrospectively. But, I would like to point out the interpretation and expression of the result of this observation. The author described that the mortality increased as BMI decreased and body fat percentage increased, showing graphic pictures for hazard ratios for death according to the changes in BMI or mean body fat (percentage). In Table 2 and 3, quintiles of BMI was associated with a significant change of mortality only in the lowest quintile in which BMI lower than 22.52 (kg/m2), and quintile of body fat percentage only in the highest quintile (>36.14%). In all other quintiles, there was no statistical difference in the mortality. Apparently mortalities were increased in those quintiles, but it did not show progressive trends considering insignificant results in other quintiles. Secondly, the graphic expression of hazard ratio used a different range for BMI and mean body fat. In that way, it seemed a bit exaggerated and could lead to misperception rather than a precise interpretation of the results described in Table 2 & 3. This study had adopted a different classification from WHO classification, but the author did not clearly noted the reason why those narrowly divided quintiles were used. When its narrow quintile was applied, graphics could be expected to show changes between those narrow ranges rather than the wide range of outliers.In a comparison of men and women in this study, the result for men shows a more stiff change in mortality. Cause-specific mortality would reveal important information in line with obesity evaluation. ReferenceRelationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality: A Cohort Study Ann Intern Med. 2016;164(8):532-541. doi:10.7326/M15-1181
Padwal R, Leslie WD, Lix LM, Majumdar SR. Relationship Among Body Fat Percentage, Body Mass Index, and All-Cause Mortality: A Cohort Study. Ann Intern Med. ;164:532–541. doi: 10.7326/M15-1181
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Published: Ann Intern Med. 2016;164(8):532-541.
Published at www.annals.org on 8 March 2016
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