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Defining Overweight and Obesity by Percent Body Fat instead of Body Mass Index

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Defining Overweight and Obesity by Percent Body Fat instead of Body Mass Index

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  • June 21, 2024
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  • 2023/2024
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1 Defining Overweight and Obesity by Percent Body Fat instead of Body Mass Index

2
3 Adam W. Potter, PhD, MBA 1, *
4 Email: adam.w.potter.civ@health.mil
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6 Geoffrey C. Chin, MD 1




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7 Email: geoffrey.c.chin.mil@health.mil
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9 David P. Looney, PhD 2
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Email: david.p.looney4.civ@health.mil
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12 Karl E. Friedl, PhD 3




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13 Email: karl.e.friedl3.civ@health.mil
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15 1Thermal and Mountain Medicine Division, U.S. Army Research Institute of Environmental
16 Medicine, 10 General Greene Avenue, Bldg 42 Natick, Massachusetts 01760-5007




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18 2Military Performance Division, U.S. Army Research Institute of Environmental Medicine, 10
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General Greene Avenue, Bldg 42 Natick, Massachusetts 01760-5007
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21 3Office of the Senior Scientist, U.S. Army Research Institute of Environmental Medicine, 10
22 General Greene Avenue, Bldg 42 Natick, Massachusetts 01760-5007
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24 * Correspondingauthor: Adam W. Potter, 10 General Greene Ave., Natick, MA 01760; phone:
25 508-206-2357; email: adam.w.potter.civ@health.mil ORCID: 0000-0003-4980-8353
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28 Word count: 1,898; Figures: 4, Tables 3
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Keywords: body fat, body mass index, BMI, metabolic syndrome
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33 Disclosure statement: The authors have no conflicts of interest to report.
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34

35 Key Points [100/100 words]
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36 Question: What are the percent body fat (%BF) metrics that equate to obesity-related health risk

37 thresholds?




© The Author(s) 2024. Published by Oxford University Press on behalf of the Endocrine Society. This is an Open
Access article distributed under the terms of the Creative Commons Attribution License
(https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in
any medium, provided the original work is properly cited. 1

,1 Findings: In a statistical sampling of the adult American population (NHANES 1999-2018)

2 which included 8,734 men and 8,184 women, BMI thresholds of overweight (BMI>25) and

3 obesity (BMI≥30) predicted 5% and 35% rates of metabolic syndrome; these same disease rates

4 were associated with 25 and 30%BF (men) and 36 and 42%BF (women), respectively.




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5 Meaning: Practical methods of body composition estimation can be used by clinicians to replace




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6 individually less precise body mass index in obesity management using threshold values of %BF




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7 provided from this study.


8




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9 Abstract [226/250 words]
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10 Objective: Thresholds for overweight and obesity are currently defined by body mass index
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11 (BMI), a poor surrogate marker of actual adiposity (percent body fat, %BF). Practical modern

12 technologies provide estimates of %BF but medical providers need outcome-based %BF
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13 thresholds to guide patients. This analysis determines %BF thresholds based on key obesity-
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14 related comorbidities, exhibited as metabolic syndrome (MetSyn). These limits were compared

15 to existing BMI thresholds of overweight and obesity. Design: Correlational analysis of data
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16 from cross sectional sampling of 16,918 adults (8,734 men and 8,184 women) from the US
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17 population, accessed by the National Health and Nutrition Examination Survey (NHANES)

18 public use datasets. Results: Individuals measured by BMI as overweight (BMI>25 kg/m2 ) and
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19 with obesity (BMI>30 kg/m2 ) included 5% and 35% of individuals with MetSyn, respectively.

20 For men, there were no cases of MetSyn below 18%BF, %BF equivalence to “overweight” (i.e.,

21 5% of MetSyn individuals) occurred at 25%BF, and “obesity” (i.e., 35% of MetSyn individuals)

22 corresponded to 30%BF. For women, there were no cases of MetSyn below 30%BF,



2

, 1 “overweight” occurred at 36%BF, and “obesity” corresponded to 42%BF. Comparison of BMI

2 to %BF illustrates the wide range of variability in BMI prediction of %BF, highlighting the

3 potential importance of using more direct measures of adiposity to manage obesity-related

4 disease. Conclusions: Practical methods of body composition estimation can now replace the




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5 indirect BMI assessment for obesity management, using threshold values provided from this




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6 study. Clinically relevant “overweight” can be defined as 25 and 36% BF for men and women,

7 respectively, and “obesity” is defined as 30 and 42% BF for men and women.




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8 Introduction




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9 Clinical health standards currently define thresholds for healthy, overweight, and obesity

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by body mass index (BMI; kg/m2 ). While BMI has long been the primary metric in clinical
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11 weight management, it has also been well recognized to be a poor surrogate marker of actual
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12 adiposity or relative body fat (%BF) (1). Practical modern technologies are beginning to provide
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13 more reliable estimates of %BF but for these to be useful, medical providers require outcome-
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14 based %BF thresholds to help guide patient health. These %BF metrics to advise patients about

15 obesity-related health risks require direct derivation from clinical health outcomes. Previous
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16 attempts to derive %BF health risk thresholds from BMI are problematic because of the

17 imprecise relationship and the relationship is further affected by factors such as age, sex,
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18 nutrition and fitness habits (2,3).
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19 Obesity-related diseases have been defined on the basis of excess adiposity, primarily via

20 deposition of lipids in liver and muscle and decreases in whole body insulin sensitivity (4).

21 However, instead of targeting the association of %BF with obesity-related diseases, “ideal

22 weight” recommendations for Americans have been generalized to associations with all-cause



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