Obesity, Adiposity Indices, and Blood Pressure; Ethnicity Does Matter
Notice bibliographique
Résumé
It is well known that there is a greater prevalence of hypertension in obese than among normal weight subjects. However, not every obese individual is hypertensive, indicating that obesity is a heterogeneous condition. Although excess fatness may contribute to high blood pressure (BP) in obese patients, the best indices of adiposity which relate to BP are still unclear. Kotchen and colleagues have investigated the relation between indices of adiposity (body mass index, waist circumference, waist-to-hip and waist-to-height ratios, percentage of body fat derived from skinfold thicknesses) and BP in normotensive and untreated hypertensive African Americans.1 BP–adiposity relationship was also evaluated in normotensive and untreated hypertensive non-Hispanic black and non-Hispanic White participants from National Health and Nutritional Examination Survey. They found that while indices of adiposity were higher in hypertensive subjects, the association between adiposity indices and BP was only seen in normotensive subjects. In a stepwise regression analysis, waist-to-hip ratio was the best adiposity parameter explaining the variation in BP in the whole population while waist circumference was the best correlate of BP in normotensive individuals. Only waist circumference was predictive of BP in untreated hypertensive individuals. The authors also concluded that the BP–adiposity relationship in hypertensive individuals may be modulated by a combination of environmental and genetic factors. The population studied by Kotchen et al. should be considered mostly overweight from a BMI viewpoint since waist circumference was only increased in hypertensive women.1 Percent body fat was low in normotensive and hypertensive men and waist-to-hip ratio was also within normal range in men and women in the Milwaukee cohort, while waist circumference was higher in the National Health and Nutritional Examination Survey cohort. Also, insulin levels or insulin resistance index was not reported. Obesity, insulin resistance, and systemic hypertension are clearly interrelated. Although the pathophysiology linking these variables is not clear, a meta-analysis supported the role of hyperinsulinemia in the pathogenesis of systemic hypertension.2 This role was corroborated in cohorts such as the San Antonio Heart Study,3 the Atherosclerosis Risk in Communities study,4 the Coronary Artery Risk Development in Young Adults study,5 and the eastern Finland cohort. Pathophysiological mechanisms linking insulin to hypertension are numerous (stimulation of the sympathetic nervous system, renal sodium retention, decreased heart rate variability, hemodynamic effects). The presence of abdominal obesity may influence the pathophysiological events linking insulin resistance to hypertension as shown by the association between BP and waist. Nevertheless, the link between insulin resistance and BP suffers from a lack of consistency, and ethnicity may be an important potential confounder. The strength of relationship between insulinemia, insulin resistance, and hypertension varies widely according to ethnic groups, since weak associations has been reported in African Americans compared with white Americans in the Atherosclerosis Risk in Communities4 and the Coronary Artery Risk Development in Young Adults study.5 Although the authors suggested that control of body weight may be more effective in the prevention compared to the treatment of hypertension, weight loss should always be mandatory in individuals with risk factors. Nevertheless, this study evokes that genetic background impact the relationship between BP and obesity. The author declared no conflict of interest.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,013 | 0,011 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,003 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».