COPINION Body composition phenotypes and obesity paradox · PINION Body composition phenotypes and obesity paradox Carla M. Pradoa, M. Cristina Gonzalezb, and Steven B. Heymsfieldc
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REVIEW
CURRENTOPINION Body composition phenotypes and obesity paradox
Copyrig
1363-1950 Copyright � 2015 Wolte
a b c
Carla M. Prado , M. Cristina Gonzalez , and Steven B. Heymsfield
Purpose of review
The obesity paradox is a highly controversial concept that may be attributed to methodological limitationsrelated to its identification. One of the primary concerns is the use of BMI to define obesity. This indexdoes not differentiate lean versus adipose tissue compartments (i.e. body composition) confounding healthconsequences for morbidity and mortality, especially in clinical populations. This review will describe thepast year’s evidence on the obesity paradox phenomenon, primarily focusing on the role of abnormalbody composition phenotypes in explaining the controversies observed in the literature.
Recent findings
In spite of the substantial number of articles investigating the obesity paradox phenomenon, less than 10%used a direct measure of body composition and when included, it was not fully explored (only adiposetissue compartment evaluated). When lean tissue or muscle mass is taken into account, the general findingis that a high BMI has no protective effect in the presence of low muscle mass and that it is the latter thatassociates with poor prognosis.
Summary
In view of the body composition variability of patients with identical BMI, it is unreasonable to rely solelyon this index to identify obesity. The consequences of a potential insubstantial obesity paradox are mixedmessages related to patient-related prognostication.
Keywords
body composition, body composition phenotypes, obesity paradox, sarcopenia, sarcopenic obesity
aDepartment of Agricultural, Food and Nutritional Science, University ofAB, Edmonton, Alberta, Canada, bPost Graduate Program in Health andBehavior, Catholic University of Pelotas, Pelotas, RS, Brazil andcPennington Biomedical Research Center, Baton Rouge, Los Angeles,USA
Correspondence to Carla M. Prado, PhD, Alberta Institute for HumanNutrition, Department of Agricultural, Food and Nutritional Science,University of Alberta, 4-002 Li Ka Shing Centre, Edmonton, AB T6G2P5, Canada. E-mail: [email protected]
Curr Opin Clin Nutr Metab Care 2015, 18:535–551
DOI:10.1097/MCO.0000000000000216
INTRODUCTION
Obesity is a widespread public health problemafflicting many countries around the world.Although obesity conveys a clear unfavourable prog-nosis for morbidity and mortality in the generalpopulation, this association seems blunted in somechronic conditions with obese individuals present-ing with a survival advantage over their counter-parts, a phenomenon termed the ‘obesity paradox’or ‘reverse epidemiology’.
The obesity paradox is a controversial conceptthat can be attributed to methodological limitationsof the studies wherein it has been observed. One ofthe criticisms is the use of anthropometrics estimatessuch as BMI to define obesity. Body weight andBMI do not depict the different proportions of leanversus adipose tissues (i.e. body composition), con-founding health consequences for morbidity andmortality, especially in clinical scenarios [1
&
]. Thisreview will describe the past year’s evidence on theobesity paradox phenomenon, primarily focusingon the role of abnormal body composition pheno-types in explaining the controversies observed inthe literature.
The obesity paradox has been reported in patientswith different types of cardiovascular disease, dia-betes, cancer, renal disease, chronic obstructivepulmonary disease (COPD) and in older age [2]. Inthese studies, survival advantages are reported inthose with increased BMI (obese compared to nor-mal weight patients), contradicting the sharpincrease in mortality with a more than 30 kg/m2
� Obesity paradox is a topic of intense interest yet withnotably contradictory findings.
� Shortcomings associated with these contradictoryfindings may be explained by the inadequacy of BMIas an obesity classifier.
� Variability in body composition phenotypes (i.e.adipose versus muscle tissues) of contemporarypopulation indicates different nutritional status even inindividuals with identical BMI.
� The use of body composition analysis indicates thatexcess adipose tissue has no protective effect in thepresence of low muscle mass.
Nutrition and physiological function
Prolonged survival with increased BMI may beexplained by a variety of factors such as these indi-viduals receiving higher rates of optimal medicalattention/treatment. The availability of energyreserves during acute catabolic illness is alsoanother plausible explanation leading to survivalbias, index event bias or reverse causation [3]. Theprotective effect of anti-inflammatory cytokines oradipokines, including soluble tumour necrosis fac-tor-alpha receptors and lipopolysaccharides, is alsohypothesized to neutralize the inflammatorymilieu of catabolic diseases [3]. Higher BMI mayalso be related to protective factors such asyounger age.
Nonetheless, several shortcomings should beconsidered when interpreting studies reportingthe obesity paradox. These include:
(1)
FIGU
fat m
536
use of incorrect reference values (lower overallBMI reference ranges) [4];
RE 1. Illustration scheme of potential differences in body cass and black represents lean mass).
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(2)
Hea
ormal ss
omp
collider stratification bias, a type of selectionbias wherein the conditioning on a variableaffected by exposure shares common causeswith the outcome producing a spurious protec-tive prognostic effect of obesity [5];
(3)
observational and cross-sectional study designs;and
(4)
inadequacy of BMI as an obesity classifier.
As discussed by Heymsfield and Cefalu [6], theuse of BMI as a health risk phenotype has severallimitations. BMI accounts for about two-thirds ofthe between-individual variability in total adiposity.In spite of the high correlation of BMI with adi-posity, a two to three-fold variation in visceral adi-posity is observed at any given BMI, illustrating howBMI is not a specific index of abnormal fat accumu-lation. Therefore, among equally overweight indi-viduals, differences in overall quantity anddistribution of adipose tissue, muscularity, nutri-tional status disease risk factors (disease severityand comorbidities), age, race and sex may explainthe greater risk for shorter survival [4,6].
Of our particular interest, and the focus of thisreview, is the use of BMI to diagnose obesity in viewof the variability in body composition phenotypesof the contemporary population. As we will discussnext, BMI does not accurately depict different com-ponents of body composition and is thereforeunable to predict the prognostic effect of individualtissues, Fig. 1.
BODY COMPOSITION PHENOYPES:DEMYSTIFYING THE OBESITY PARADOX?
Higher BMI is generally found to be associated withgreater muscle mass and strength. This is because fat
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Obese with high lean mass
osition in individuals with identical BMI (grey represents
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Body composition phenotypes and obesity paradox Prado et al.
and lean masses are expected to grow in harmonywith each other. Although this may be true for themajority of individuals, the assessment of in-vivobody composition has highlighted that this is not aubiquitous phenomenon. High body weight (henceBMI) and fat mass can coexist with obesity, a syn-drome known as ‘sarcopenic obesity’. In fact, theconcurrent appearance of low muscle and high adi-pose tissue can occur at any given BMI across the agespectrum [7,8]. We used North-American popu-lation-cohort data to illustrate the variability inbody composition phenotypes at different agesand across the BMI categories. With our proposedclassification criteria to define abnormal body com-position, we reported that normal-weight individ-uals could present with diverse body compositionphenotypes such as high adiposity–high muscular-ity, low adiposity–low muscularity or even highadiposity–low muscularity (i.e. analogous to sarco-penic obesity). Each of these phenotypes is likely tobe associated with diverse nutritional status.
Oreopoulos et al. [9] reported that BMI misclas-sified 41% of body fat status in patients with chronicheart failure. A higher muscularity and/or loweradiposity were independently associated withadvantageous prognostic factors in these patients.Similar findings were more recently confirmed inpatients with cancer: those with excess fat mass weremisclassified as overweight or even normal weightaccording to BMI criteria [10
&
]. Such misclassifi-cation may explain the controversial results of theobesity paradox reported in studies using BMI as aclassification criterion for obesity. These findingshighlight the need for further studies investigatingthe obesity paradox phenomenon in the context ofbody composition assessment.
THE PAST YEAR EVIDENCE AT A GLANCE
The obesity paradox may certainly be considered atopic of high interest in the scientific communitywith a total of 71 published articles in the past yearalone. Within this time frame, we found 25 reviewarticles, four meta-analyses and 42 original articlesdiscussing this phenomenon. Out of the originalarticles (N¼42), 31 used only BMI to classifyobesity, whereas seven used a surrogate assessmentof body composition (e.g. waist or hip circumfer-ence, skinfold thickness) and four used a directassessment of body composition.
Studies using BMI as the sole indicator ofobesity
Table 1 depicts a summary of the studies in whichonly BMI was used to define obesity [3,5,11–39].
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Patient cohorts included various forms of cardio-vascular diseases, investigated in the majority of thestudies (N¼21/31). Other patient cohorts includedthose with rheumatoid arthritis, peptic ulcer, per-itonitis and sepsis, diabetes mellitus type 2, demen-tia, COPD, lung resection, mechanical ventilationand a cohort of nondiseased individuals.
Table 1 summarizes that the obesity paradox(higher BMI associated with better prognosis) wasreported in 13 out of 31 studies. Out of these, twostudies observed this association in overweight butnot obese individuals [14,18]; one observed it inmen but not women [27]; one in short but notlong-term outcomes (mortality rate) [34], and onein some outcomes (myocardial infarction and sep-ticemia) but not survival [26]. Mixed findings werereported in two studies when patients were stratifiedby ventilated versus nonventilated group (only theformer showing obesity paradox) [30] and low ver-sus high cardiorespiratory fitness [13], with only theformer showing the paradox. The remaining (andmajority) of the studies failed to demonstrate aprognostic advantage to having excess body weight(Table 1).
The four meta-analyses reported the following:Sharma et al. [40] investigated the relationship ofBMI with all-cause and cardiovascular mortality andhospitalization in six studies of patients with chronicheart failure. The authors concluded that risk forcardiovascular mortality and incidence of hospital-ization was lowest in overweight patients but foundno differences in all-cause mortality. Severe obesitywas associated with poor overall cardiovascular out-comes, suggesting that apparent effect of adipositydoes not occur at the extreme levels of obesity. In aseparate meta-analysis of 36 studies, the same groupinvestigated the obesity paradox after coronary arterydisease revascularization procedures [41]. Whenlooking at total mortality, cardiovascular mortalityand myocardial infarction, only cardiovascularmortality was found to be lower in overweightpatients. In both studies, detailed data on cardio-vascular risk factors, severity/stage of disease or unin-tentional weight loss were not available, which doesnot rule out the possibility of residual confoundingeffects in the reported results.
Niedziela et al. [42] reported the relationshipbetween BMI and total mortality in 26 studies ofpatients after acute coronary syndrome. The authorsconcluded that overweight, obese and severelyobese patients presented with lower mortality thanthose with normal BMI. The authors noted thatalthough obesity was associated with comorbidities,these patients were younger and had less bleedingcomplications, which could have influencedsurvival.
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Body composition phenotypes and obesity paradox Prado et al.
Ahmadi et al. [43] investigated the obesity para-dox in kidney transplant recipients in four studies,reporting a higher mortality in obese patients usingpretransplantation BMI. Notably, all of these meta-analysis studies reported a higher risk of shortersurvival among underweight patients. Ahmadiet al. [43] highlighted that unlike obesity, beingunderweight consistently predicted survival. There-fore, there are paradoxical or differing resultssuggesting that the presence of obesity paradox isunlikely in such a scenario [43].
Using data from 89 studies with a total of1 300 794 patients wherein risk estimates were pro-vided for short and long-term mortality on cardio-vascular events, Wang et al. [44] reported a J-shapedrelationship between mortality and BMI in patientswith coronary artery disease. Underweight patientspresented with the highest risk and the overweightand obese with the lowest. Nonetheless, inconsist-ent findings were reported when the long-term datawere evaluated. The long-term inverse relationshipbetween BMI and mortality was attenuated, disap-pearing after 5 years of follow-up. Grades II and IIIobesity were associated with lower risk of short-termmortality but higher risk after 5 years of follow-up.
Studies using surrogate assessments ofbody composition
Additional anthropometric measurements such aswaist and/or hip circumference, skinfold thicknessmeasurements and circumferences were used inseven studies, in which three reported the obesityparadox (one observing it in men only) and theremaining disproving such phenomenon (Table 2)[45–55]. Using an inception cohort of adults withdiabetes, Bozorgmanesh et al. [45] highlighted theneed of adjusting for a measure of central adipositywhen investigating the effect of obesity andmortality. The lack of a value for waist circumfer-ence would have led to an overestimation of themortality associated with an increased BMI in theirdatabase of newly diagnosed patients with diabetes.The authors noted that there is a ‘BMI-paradox’,which is not a sufficient marker of obesity.
The need for further measurements of nutri-tional assessment when investigating the obesityparadox was highlighted in the study by Gastelur-rutinia et al. [47
&&
]. In patients with heart failure,nutritional status (undernourished) was an inde-pendent prognostic factor above and beyond BMIand percentage body fat (calculated using surrogatetools). Therefore, in this study, BMI masked truenutritional status.
Using arm circumferences and skinfoldmeasurements of patients receiving elective surgery,
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Rodriguez-Garcia et al. [49] found no differences innosocomial infection and length of hospital staycomparing obese and nonobese patients; nonethe-less, the authors have not controlled for confound-ing variables; only bivariate analysis was conducted.In patients with acute coronary syndrome, Shehabet al. [50] showed that in-hospital and peri-hospitalmortality was not associated with weight, BMI orwaist circumference.
Studies using body compositionassessments
There is a clear need for further body compositionassessment studies to elucidate the contradictoryevidence on the obesity paradox phenomenon asonly four have been published in the past year.Among these, the methodologies utilized were com-puted tomography (CT, two studies), dual-energyX-ray absorptiometry (DXA) or bioelectrical impe-dance analysis (BIA), Table 2.
In 72 patients with COPD, survival was notdifferent between higher versus lower BMI patients(although a trend towards longer survival wasobserved in those with higher BMI) [52
&&
]. Over-weight and obese patients had better lung function,exercise capacity and larger muscle cross-sectionalarea than those with normal BMI. These variableswere able to confound the trend of improved sur-vival in those with excess BMI.
An interesting study in older adults with type 2diabetes; Murphy et al. [54
&&
] used CT-assessed bodycomposition and functional assessments to test theassociation between these variables and mortality.Using multivariate analysis adjusted for demo-graphic and diabetes-risk factors, they reportedhigher risk in normal-weight patients than over-weight ones. The authors further performed amediation analysis to test if adipose tissue, musclesize and physical function would affect the associ-ations between BMI and mortality. From thisanalysis, thigh muscle size mediated 46% of theeffect of the higher risk found in normal-weightpatients. When comparing four groups: over-weight/normal weight and high/low muscle(according to the respective sex-specific median),the authors concluded that being overweight wasonly protective in patients with high muscle massand that the highest mortality was found in the twolow muscle mass groups (either in patients withnormal weight or overweight). These resultsare similar to what has been reported in cancerpatients [10
&
]. Using BIA to assess body compo-sition, Gonzalez et al. [10
&
] reported that the obesityparadox was only present in cancer patients whenobesity was defined by BMI. BMI was not able to
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identify the majority of patients with excess fat massand low muscle mass was an independent risk factorfor higher mortality. Excess fat mass had no protec-tive effect in the presence of low muscle mass andthe shorter survival time was indeed observed in thesarcopenic obesity group.
Two studies noted the obesity paradox usingdirect assessment of body composition. In the studyby Hong et al. [53], higher visceral adiposity assessedby CT scan and not BIA-assessed total fat mass wasassociated with reduced all-cause mortality in eld-erly Asian individuals (mean age 76 years). All-causemortality was lowest within the highest and thirdBMI and visceral adiposity quartiles, respectively.Furthermore, visceral adiposity was a marker formortality in a U-shaped pattern. Interestingly andunfortunately, the authors have not explored theeffect of fat free mass (and hence muscle mass) intheir model, even though that was assessed by BIA.CT-assessed muscle mass was also not evaluated. Asthe authors discussed, muscle mass is an importantvariable that can explain their findings. Finally, thestudy by Perna et al. [55] examines the associationamong low muscle mass, adiposity and metabolicmarkers in Italian older individuals. In a complexstatistical analysis called canonical correlationanalysis and structural equation modelling, individ-ual scores of metabolic profile were created andcorrelated with muscle mass. The authors noted anegative association between sarcopenia severityand adiposity/metabolic profile, indicating a protec-tive effect of adiposity on muscle loss. Therefore,although their results confirmed the obesity para-dox, an increase of adiposity and levels of metabolicparameters were protective in respect to muscle loss[55].
CONCLUSION
A perpetuation of the contradictory findings relatedto the obesity paradox is highlighted in this review,independent of the definition of obesity being solelybased on BMI, surrogate or direct assessments ofbody composition.
There is enough evidence in the literature high-lighting the value of body composition assessment toevaluate and predict nutritional status, and emergingevidence that body composition phenotypes maydemystify the obesity paradox phenomenon. None-theless, less than 10% (four out of 42) of the originalarticles published in the past 12 months included adirect assessment of body composition and, amongthese, a full description of compartments (e.g. musclemass) was not conducted/explored.
In view of the body composition variability ofpatients with identical BMI, particularly in clinical
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Nutrition and physiological function
populations, it is unreasonable to rely solely on thisindex as a marker to identify obesity. Furthermore,differences in fluid shifts that may occur in theseclinical conditions may also impact the accuracy ofBMI [47
The use of sophisticated body compositionassessment tools is still limited (especially in epide-miological settings). Notwithstanding, it is unlikelythat we will substantially advance our knowledgewithout the use of this science. As we have pre-viously discussed [1
&
,7], Hippocrates could havemeasured body weight and BMI. We are in an erain which sophisticated tools are needed and in linewith any other evolving field of health-relatedresearch.
If body composition phenotypes can indeedelucidate the dichotomous relationship betweenBMI and prognostication in a variety of clinicaland nonclinical conditions, the need is urgent forsuch a research approach. The consequences of apotential insubstantial obesity paradox are mixedmessages advising individuals to become obese inthe hopes of improving outcomes. Finally, adjustingfor important confounding bias originating fromeach specific condition under study is also import-ant and potentially mediators of the risk factorassociated with obesity.
Acknowledgements
The authors would like to acknowledge Isabella Barbosa,Sarah Purcell, Camila Orsso and Bianca Caroline Orssofor their assistance in creating drafting and/or formattingthe tables, figure and references.
Financial support and sponsorship
None.
Conflicts of interest
There are no conflicts of interest.
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& of special interest&& of outstanding interest
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52.&&
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54.&&
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