The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study

Jackson, A. S.; Pr, Stanforth; Gagnon, Jacques; Rankinen, Tuomo; Leon, AS; Rao, D. C.; Skinner, J. S.; Bouchard, Claude; Jh, Wilmore

doi:10.1038/sj.ijo.0802006

Cited by 582 publications

(461 citation statements)

References 18 publications

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“…However, in this last study, the range of BMI values was limited as virtually all subjects had a BMI of o35 kg m À2 . Two more recent findings addressing this issue on populations in the United States of America 16 and Europe 17 are in agreement with the early demonstration by Webster et al 14 that the BMI-FM% relationship is curvilinear in both men and women, as shown in Figure 4. This nonlinear response is expected from the influence of individuals with BMI much above 35 kg m À2 .…”

Section: Bmi-fm% Relationship: Linear or Curvilinear?supporting

confidence: 78%

Body composition phenotypes in pathways to obesity and the metabolic syndrome

et al. 2010

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Dynamic changes in body weight have long been recognized as important indicators of risk for debilitating diseases. While weight loss or impaired growth can lead to muscle wastage, as well as to susceptibility to infections and organ dysfunctions, the development of excess fat predisposes to type 2 diabetes and cardiovascular diseases, with insulin resistance as a central feature of the disease entities of the metabolic syndrome. Although widely used as the phenotypic expression of adiposity in population and gene-search studies, body mass index (BMI), that is, weight/height 2 (H 2 ), which was developed as an operational definition for classifying both obesity and malnutrition, has considerable limitations in delineating fat mass (FM) from fat-free mass (FFM), in particular at the individual level. After an examination of these limitations within the constraints of the BMI-FM% relationship, this paper reviews recent advances in concepts about health risks related to body composition phenotypes, which center upon (i) the partitioning of BMI into an FM index (FM/H 2 ) and an FFM index (FFM/H 2 ), (ii) the partitioning of FFM into organ mass and skeletal muscle mass, (iii) the anatomical partitioning of FM into hazardous fat and protective fat and (iv) the interplay between adipose tissue expandability and ectopic fat deposition within or around organs/tissues that constitute the lean body mass. These concepts about body composition phenotypes and health risks are reviewed in the light of race/ethnic variability in metabolic susceptibility to obesity and the metabolic syndrome.

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Section: Bmi-fm% Relationship: Linear or Curvilinear?supporting

confidence: 78%

Body composition phenotypes in pathways to obesity and the metabolic syndrome

et al. 2010

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“…This study was conducted in Caucasian subjects and would need to be extended to other populations to determine race-specific differences, as regarding BF% ranges for a given BMI and if the significant correlations to the cardiometabolic risk factors are (i) maintained, and (ii) if so, establish to which degree. 9,10,58 Another potential limitation of the present study is that smoking and medication were generally not available. Accordingly, we could not adjust for the potential confounding effects of these variables.…”

Section: Discussionmentioning

confidence: 99%

“…[4][5][6][7] These cutoffs are very useful in epidemiological studies 8 but in spite of its wide use BMI is only a surrogate measure of body fatness and does not provide an accurate measure of body composition. [8][9][10][11][12][13][14][15][16][17][18][19][20][21] Noteworthy, obesity is defined as an excess accumulation of body fat, with the amount of this excess fat actually being responsible for most obesity-associated health risks. 22 Obesity increases the risk of cardiovascular diseases and type 2 diabetes 23,24 at the same time as imposing functional limitations in a number of subjects, which translate into a reduced quality of life as well as life expectancy.…”

Section: Introductionmentioning

confidence: 99%

Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity

et al. 2011

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Context: Body mass index (BMI) is widely used as a measure of overweight and obesity, but underestimates the prevalence of both conditions, defined as an excess of body fat. Objective: We assessed the degree of misclassification on the diagnosis of obesity using BMI as compared with direct body fat percentage (BF%) determination and compared the cardiovascular and metabolic risk of non-obese and obese BMI-classified subjects with similar BF%. Design: We performed a cross-sectional study. Subjects: A total of 6123 (924 lean, 1637 overweight and 3562 obese classified according to BMI) Caucasian subjects (69% females), aged 18-80 years. Methods: BMI, BF% determined by air displacement plethysmography and well-established blood markers of insulin sensitivity, lipid profile and cardiovascular risk were measured. Results: We found that 29% of subjects classified as lean and 80% of individuals classified as overweight according to BMI had a BF% within the obesity range. Importantly, the levels of cardiometabolic risk factors, such as C-reactive protein, were higher in lean and overweight BMI-classified subjects with BF% within the obesity range (men 4.3 ± 9.2, women 4.9 ± 19.5 mg l À1 ) as well as in obese BMI-classified individuals (men 4.2 ± 5.5, women 5.1 ± 13.2 mg l À1 ) compared with lean volunteers with normal body fat amounts (men 0.9 ± 0.5, women 2.1 ± 2.6 mg l À1 ; Po0.001 for both genders). Conclusion: Given the elevated concentrations of cardiometabolic risk factors reported herein in non-obese individuals according to BMI but obese based on body fat, the inclusion of body composition measurements together with morbidity evaluation in the routine medical practice both for the diagnosis and the decision-making for instauration of the most appropriate treatment of obesity is desirable.

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“…27 use of Bf determination Although BMI is the most common method to define overweightness/obesity, especially in major epidemiologic studies, this method has been criticized because it may not always reflect true body fatness, and BMI/body fatness may differ considerably among the various ages, sexes, and races. [9][10][11][12][13]28 Part of the explanation for the unexpected association between BMI and outcomes in CHD and other CV diseases could be due to the poor diagnostic performance of BMI to define body fatness and lean body mass, factors that could be associated with opposing outcomes in CV diseases. 1,[8][9][10][11][12][13][14]29 In fact, the group from Mayo Clinic has previously demonstrated that BMI performs suboptimally in predicting obesity as defined by BF (>25% in men and >35% in women) in a CHD population.…”

Section: Discussionmentioning

confidence: 99%

Body Composition and Coronary Heart Disease Mortality—An Obesity or a Lean Paradox?

Lavie¹,

Schutter²,

Patel³

et al. 2011

Mayo Clinic Proceedings

138

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Body Composition and Heart disease mortalityFor personal use. Mass reproduce only with permission from Mayo Clinic Proceedings a .D espite the well-known adverse affects of obesity on almost all aspects of coronary heart disease (CHD) and CHD risk factors, including hypertension (HTN), plasma lipids, inflammation, glucose abnormalities, insulin resistance, metabolic syndrome and type 2 diabetes mellitus (T2DM), as well as left ventricular hypertrophy (LVH), many studies of cohorts with established cardiovascular (CV) disease, including heart failure (HF), HTN, as well as CHD, have demonstrated an inverse relationship between obesity, generally determined by body mass index (BMI [calculated as the weight in kilograms divided by the height in meters squared]), on subsequent mortality, referred to as the obesity paradox. 1,2 The obesity paradox has also been demonstrated in non-CV studies that included patients with advanced renal disease and the elderly. 3,4 Many large studies of cohorts with CHD have demonstrated this obesity paradox, [5][6][7] which has also been demonstrated in a large meta-analysis by Romero-Corral et al 8 from Mayo Clinic, who analyzed 40 cohort studies totaling more than 250,000 patients with CHD grouped according to BMI.Although BMI is the most frequently used method to assess overweightness/obesity, especially in large epidemiologic studies, this method has been criticized because BMI does not always reflect true body fatness. 1,2,9-14 Some investigators have theorized that at least part of the inconsistent relationship between obesity and major CV disease events, including mortality, may be due to the inaccurate diagnosis of obesity by the BMI assessment and that defining obesity by other methods, including waist circumference, waist/hip ratio, as well as percent body fat (BF) may be more accurate. 2,[9][10][11][12][13] We have recently demonstrated this obesity paradox in a cohort of CHD patients using both BMI and BF determinations. 14 To our knowledge, no prior studies have determined the independent effects of both BMI and BF on mortality in a cohort of CHD patients. Therefore, in the current evaluation, we determined the combined and independent impact of both BMI and BF on mortality in a cohort with stable CHD. PATIENTS AND METHODSWe retrospectively reviewed the case records of 581 consecutive patients with stable CHD who were referred for potential entry into formal cardiac rehabilitation programs between January 1, 2000, and July 31, 2005, and who had baseline anthropometric, lipid, and clinical data, as we have previously described. 14 Patients were divided into low (<25) and high (≥25) BMI. Elevated BF has been defined as greater than 25% in men and greater than 35% in women, 15,16 so patients were also divided into low (≤25% men and ≤35% women) and high BF (>25% men and >35% women Objective: To determine the combined effects of body mass index (BMI) and body fat (BF) on prognosis in coronary heart disease (CHD) to better understand the obesity paradox. Patients and MethOds:We s...

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The effect of sex, age and race on estimating percentage body fat from body mass index: The Heritage Family Study

Cited by 582 publications

References 18 publications

Body composition phenotypes in pathways to obesity and the metabolic syndrome

Body composition phenotypes in pathways to obesity and the metabolic syndrome

Body mass index classification misses subjects with increased cardiometabolic risk factors related to elevated adiposity

Body Composition and Coronary Heart Disease Mortality—An Obesity or a Lean Paradox?

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