Catherine M Phillips1, Ivan J Perry. 1. Health Research Board Centre for Diet and Health Research, Room 4.033, Department of Epidemiology and Public Health, Western Gateway Building, University College Cork, Cork, Ireland. c.phillips@ucc.ie.
Abstract
CONTEXT: Inflammation is a potential mechanism linking obesity and cardiometabolic risk. Limited data on inflammatory markers in metabolically healthy obese and nonobese individuals exist. OBJECTIVE: The aim of the study was to investigate the extent to which differences between metabolically healthy and unhealthy obese and nonobese adults, defined using a range of metabolic health definitions, are correlated with a range of inflammatory markers. DESIGN: A cross-sectional sample of 2047 men and women aged 45-74 years participated in the study. Participants were classified as obese (body mass index ≥ 30 kg/m(2)) and nonobese (body mass index < 30 kg/m(2)). Metabolic health status was defined using 5 existing metabolic health definitions based on a range of cardiometabolic abnormalities. Serum acute-phase reactants, adipocytokines, proinflammatory cytokines, and white blood cell counts were determined. RESULTS: According to most definitions, metabolically healthy obese and nonobese individuals presented with lower concentrations of complement component 3, C-reactive protein, TNF-α, IL-6, and plasminogen activator inhibitor-1; higher adiponectin levels; and reduced white blood cell count compared to their metabolically unhealthy counterparts. Logistic regression analysis identified greater likelihood of metabolically healthy obesity among individuals with lower levels of complement component 3 (odds ratios [ORs], 2-3.5), IL-6 (ORs, 1.7-2.9), plasminogen activator inhibitor-1 (ORs, 1.7-2.9), and white blood cells (ORs, 2.1-2.5) and higher adiponectin concentrations (ORs, 2.6-4.0). CONCLUSIONS: Favorable inflammatory status is positively associated with metabolic health in obese and nonobese individuals. These findings are of public health and clinical significance in terms of screening and stratification based on metabolic health phenotype to identify those at greatest cardiometabolic risk for whom appropriate therapeutic or intervention strategies should be developed.
CONTEXT: Inflammation is a potential mechanism linking obesity and cardiometabolic risk. Limited data on inflammatory markers in metabolically healthy obese and nonobese individuals exist. OBJECTIVE: The aim of the study was to investigate the extent to which differences between metabolically healthy and unhealthy obese and nonobese adults, defined using a range of metabolic health definitions, are correlated with a range of inflammatory markers. DESIGN: A cross-sectional sample of 2047 men and women aged 45-74 years participated in the study. Participants were classified as obese (body mass index ≥ 30 kg/m(2)) and nonobese (body mass index < 30 kg/m(2)). Metabolic health status was defined using 5 existing metabolic health definitions based on a range of cardiometabolic abnormalities. Serum acute-phase reactants, adipocytokines, proinflammatory cytokines, and white blood cell counts were determined. RESULTS: According to most definitions, metabolically healthy obese and nonobese individuals presented with lower concentrations of complement component 3, C-reactive protein, TNF-α, IL-6, and plasminogen activator inhibitor-1; higher adiponectin levels; and reduced white blood cell count compared to their metabolically unhealthy counterparts. Logistic regression analysis identified greater likelihood of metabolically healthy obesity among individuals with lower levels of complement component 3 (odds ratios [ORs], 2-3.5), IL-6 (ORs, 1.7-2.9), plasminogen activator inhibitor-1 (ORs, 1.7-2.9), and white blood cells (ORs, 2.1-2.5) and higher adiponectin concentrations (ORs, 2.6-4.0). CONCLUSIONS: Favorable inflammatory status is positively associated with metabolic health in obese and nonobese individuals. These findings are of public health and clinical significance in terms of screening and stratification based on metabolic health phenotype to identify those at greatest cardiometabolic risk for whom appropriate therapeutic or intervention strategies should be developed.
Authors: Juan G Juárez-Rojas; Ivan Torre-Villalvazo; Aida X Medina-Urrutia; Juan Reyes-Barrera; Víctor H Sainz-Escárrega; Carlos Posadas-Romero; Alejandro Macías-Cruz; Esteban Jorge-Galarza Journal: Int J Obes (Lond) Date: 2019-12-02 Impact factor: 5.095
Authors: Harish Dharuri; Peter A C 't Hoen; Jan B van Klinken; Peter Henneman; Jeroen F J Laros; Mirjam A Lips; Fatiha El Bouazzaoui; Gert-Jan B van Ommen; Ignace Janssen; Bert van Ramshorst; Bert A van Wagensveld; Hanno Pijl; Ko Willems van Dijk; Vanessa van Harmelen Journal: Diabetologia Date: 2014-08-07 Impact factor: 10.122