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Enregistrement W4362590476 · doi:10.1016/j.eclinm.2023.101935

Does this person have obesity?

2023· article· en· W4362590476 sur OpenAlexaffabout
Arya M. Sharma

Notice bibliographique

RevueEClinicalMedicine · 2023
Typearticle
Langueen
DomaineHealth Professions
ThématiqueObesity and Health Practices
Établissements canadiensUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésMedicineObesityInternal medicine

Résumé

récupéré en direct d'OpenAlex

According to the World Obesity Federation, obesity is a chronic, relapsing, progressive disease.1Bray G.A. Kim K.K. Wilding J.P.H. World Obesity FederationObesity: a chronic relapsing progressive disease process. A position statement of the World Obesity Federation.Obes Rev. 2017; 18: 715-723https://doi.org/10.1111/obr.12551Crossref PubMed Scopus (675) Google Scholar This view of obesity, however, is not without controversy. Opinions range from “fat acceptance activists”, who argue that the health impact of excess body fat are exaggerated and a cover for cultural and aesthetic prejudices against people who live in large bodies, to the Health At Every Size (HAES®) movement, which acknowledges the health impact of excess body weight but is vehemently opposed to any form of “weight-loss” as a treatment. Others see the obesity epidemic as one of the largest health crisis of our times, requiring dedicated efforts at prevention and evidence-based weight-loss treatments. The controversy of whether obesity is a disease is in part fuelled by its rather arbitrary historical definition, which relies on cut-points for body mass index (BMI). Thus, in Caucasians, obesity has been defined as a BMI equal to or greater than 30 kg/m2. Although health risk rises proportionally with an increase in BMI, when applied to an individual, BMI is neither particularly sensitive nor specific in terms of assessing current health status.2Sharma A.M. Campbell-Scherer D.L. Redefining obesity: beyond the numbers.Obesity. 2017; 25 (PMID: 28349662): 660-661https://doi.org/10.1002/oby.21801Crossref PubMed Scopus (34) Google Scholar This is not surprising, as BMI, based on height and weight, is not a reliable measure of body fat, nor does it capture body fat distribution, adipose-tissue morphology, or adipose-tissue inflammation, all of which play important roles in the health risks associated with excess body weight.3Koenen M. Hill M.A. Cohen P. Sowers J.R. Obesity, adipose tissue and vascular dysfunction.Circ Res. 2021; 128: 951-968https://doi.org/10.1161/CIRCRESAHA.121.318093Crossref PubMed Scopus (148) Google Scholar Thus, for example, an elevated waist-to-hip ratio is associated with increased risk of heart disease across the entire spectrum of BMI, with BMI itself adding little to the equation.4Yusuf S. Hawken S. Ounpuu S. et al.INTERHEART Study InvestigatorsObesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study.Lancet. 2005; 366: 1640-1649https://doi.org/10.1016/S0140-6736(05)67663-5Summary Full Text Full Text PDF PubMed Scopus (2251) Google Scholar Indeed, it is possible to identify rather healthy individuals even amongst those with higher BMIs (“fat but fit”). Conversely, there are individuals with metabolic abnormalities (e.g. pre-diabetes or non-alcoholic fatty liver disease) who currently fall below the conventional BMI cut-offs for obesity (“thin-but-metabolically-obese”), but would likely stand to benefit from weight loss. Recognition of the limitations of BMI has spawned the proposal of several disease staging systems for obesity that rely on the demonstration of health impairments rather than on anthropometric measures alone. These include the King's System,5Aasheim E.T. Aylwin S.J. Radhakrishnan S.T. et al.Assessment of obesity beyond body mass index to determine benefit of treatment.Clin Obes. 2011; 1: 77-84Crossref PubMed Google Scholar the cardiometabolic staging system endorsed by the American Association of Clinical Endocrinologists/American College of Endocrinology,6Guo F. Moellering D.R. Garvey W.T. The progression of cardiometabolic disease: validation of a new cardiometabolic disease staging system applicable to obesity.Obesity. 2014; 22: 110-118Crossref PubMed Scopus (118) Google Scholar and the Edmonton Obesity Staging System (EOSS).7Sharma A.M. Kushner R.F. A proposed clinical staging system for obesity.Int J Obes. 2009; 33: 289-295Crossref PubMed Scopus (386) Google Scholar EOSS, which defines obesity stage based on the presence of varying degrees of mental, medical or functional impairments of health, has been shown to be a better predictor of mortality than BMI or waist circumference.8Padwal R.S. Pajewski N.M. Allison D.B. Sharma A.M. Using the Edmonton obesity staging system to predict mortality in a population-representative cohort of people with overweight and obesity.CMAJ (Can Med Assoc J). 2011; 183: E1059-E1066https://doi.org/10.1503/cmaj.110387Crossref PubMed Scopus (245) Google Scholar Indeed, for a given EOSS stage, individual mortality risk appears similar irrespective of BMI. Higher EOSS stages have also been associated with greater peri-operative risk in individuals with similar BMI.9Chiappetta S. Stier C. Weiner R.A. members of StuDoQ|MBE of Deutsche Gesellschaft für Allgemein- und Viszeralchirurgie/StuDoQThe Edmonton obesity staging system predicts perioperative complications and procedure choice in obesity and metabolic surgery-a german nationwide register-based cohort study (StuDoQ|MBE).Obes Surg. 2019; 29: 3791-3799https://doi.org/10.1007/s11695-019-04015-yCrossref PubMed Scopus (19) Google Scholar The recent 2020 Canadian Clinical Practice Guidelines for adults defines obesity as "a prevalent, complex, progressive and relapsing chronic disease characterized by the presence of excess or abnormal body fat (adiposity) that impairs health".10Wharton S. Lau D.C.W. Vallis M. et al.Obesity in adults: a clinical practice guideline.CMAJ (Can Med Assoc J). 2020; 192: E875-E891https://doi.org/10.1503/cmaj.191707Crossref PubMed Scopus (334) Google Scholar The key operative word here is "impairs", so to meet the criteria of a disease, there has to be a demonstrable impairment in health. A person with a BMI above the accepted cutoff, who is otherwise healthy, would, by this definition, be considered to have adiposity but not obesity. Although BMI and other anthropometric measures (e.g. waist circumference), may be used to screen for obesity, they should not be used to make the diagnosis. In practical terms, this definition requires the health professional to answer the following question: Does this patient present with a health problem that is likely to improve with weight loss? If the answer is “yes”, then the patient has obesity. If not, then the patient may just have adiposity, which may well at some stage progress to overt obesity (hence the suggestion to refer to these individuals as having pre-obesity). Such an approach to diagnosing obesity would of course require a clinical assessment of each patient by a qualified health practitioner. Only a comprehensive interview together with a physical exam as well as relevant laboratory and imaging tests would establish (or rule out) the diagnosis “obesity” in a given individual. While this clearly makes the diagnosis of obesity more cumbersome, it ensures that otherwise healthy individuals are no longer labeled as having obesity simply based on their size. Perhaps, more importantly, individuals presenting with health issues that are clearly linked to or likely to improve with weight loss, can be diagnosed with having obesity (and thus qualifying for obesity treatments), even when they fall below the conventional BMI cutoffs. While this introduces an element of clinical judgment into the diagnosis, this is not uncommon in medical practice, where clinical judgment is often called upon in determining the presence and severity of a medical issue and the best course of action. Ultimately, the goal of making a proper diagnosis is to determine the right course of action for a given individual. In the case of someone presenting with a health problem closely linked to excess weight, for which we have strong evidence that weight-loss would improve it (e.g. hypertension, type 2 diabetes, obstructive sleep apnoea, etc.), we would see a “primary” indication for obesity treatment, i.e. successful reduction in body weight can essentially solve the problem (Fig. 1). However, we may also be confronted with a patient who presents with a health problem, not causally linked to obesity, but which is aggravated by or more difficult to manage due to the presence of excess weight (e.g. someone with excess weight who sustains an injury or contracts COVID). Such an individual could be considered to have a “secondary” indication for obesity treatment. While weight-loss will not solve the underlying problem, it may make management and recovery easier. Finally, we may consider individuals with excess weight, who present with a health problem that is neither related to nor likely to improve with weight loss. This person may be considered to have a “tertiary” indication for obesity treatment, which although perhaps leading to an overall improvement in health, would have no impact on the presenting complaint. In conclusion, while obesity is increasingly recognised as a chronic relapsing chronic disease in its own right, deserving of appropriate medical treatment, the diagnosis of obesity should be based on more than numbers on a scale or measuring tape. Rather, the clinical diagnosis of obesity should be based on a comprehensive clinical assessment of the patient to determine the presence of health impairments likely to improve with effective obesity management. AMS is the sole author and conceptualized, wrote, reviewed and edited the commentary. The author has previously received consulting and/or speaking honoraria from Novo Nordisk, Eli Lilly, Boehringer Ingelheim, Johnson & Johnson, Allurion and Xeno Biosciences. AMS declares no conflict of interest with the current commentary.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesCharge utile insuffisante (le modèle a refusé de juger)
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,249
Score d'incertitude au seuil0,979

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0050,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0220,043

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,197
Tête enseignante GPT0,538
Écart entre enseignants0,341 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; les deux têtes enseignantes s’accordent sur ce qui est montré ici.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2023
Routes d'admission2
Résumé présentoui

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