ABSTRACT
Introducción y objetivos: Algunas medidas antropométricas muestran mayor capacidad que otras para discriminar la presencia de factores de riesgo cardiovascular. Este trabajo estima la magnitud de la asociación de diversos indicadores antropométricos de obesidad con hipertensión, dislipemia y prediabetes (glucemia basal o glucohemoglobina alteradas). Métodos: Análisis transversal de la información recogida en 2.022 sujetos del estudio PREDAPS (etapa basal). Se definió obesidad general como índice de masa corporal ≥ 30 kg/m2 y obesidad abdominal con 2 criterios: a) perímetro de cintura (PC) ≥ 102 cm en varones/PC ≥ 88 cm en mujeres, y b) índice cintura/estatura (ICE) ≥ 0,55. La magnitud de la asociación se estimó mediante regresión logística. Resultados: La hipertensión arterial mostró la asociación más alta con la obesidad general en mujeres (OR = 3,01; IC95%, 2,24-4,04) y con la obesidad abdominal según el criterio del ICE en varones (OR = 3,65; IC95%, 2,66-5,01). La hipertrigliceridemia y los valores bajos de colesterol unido a lipoproteínas de alta densidad mostraron la asociación más alta con obesidad abdominal según el criterio del ICE en mujeres (OR = 2,49; IC95%, 1,68-3,67 y OR = 2,70; IC95%, 1,89-3,86) y la obesidad general en varones (OR = 2,06; IC95%, 1,56-2,73 y OR = 1,68; IC95%, 1,21-2,33). La prediabetes mostró la asociación más alta con obesidad abdominal según el criterio del ICE en mujeres (OR = 2,48; IC95%, 1,85-3,33) y con obesidad abdominal según el criterio del PC en varones (OR = 2,33; IC95%, 1,75-3,08). Conclusiones: Los indicadores de obesidad abdominal mostraron la mayor asociación con la presencia de prediabetes. La relación de los indicadores antropométricos con hipertensión y con dislipemia mostró resultados heterogéneos (AU)
Introduction and objectives: Some anthropometric measurements show a greater capacity than others to identify the presence of cardiovascular risk factors. This study estimated the magnitude of the association of different anthropometric indicators of obesity with hypertension, dyslipidemia, and prediabetes (altered fasting plasma glucose and/or glycosylated hemoglobin). Methods: Cross-sectional analysis of information collected from 2022 participants in the PREDAPS study (baseline phase). General obesity was defined as body mass index ≥ 30 kg/m2 and abdominal obesity was defined with 2 criteria: a) waist circumference (WC) ≥ 102 cm in men/WC ≥ 88 cm in women, and b) waist-height ratio (WHtR) ≥ 0.55. The magnitude of the association was estimated by logistic regression. Results: Hypertension showed the strongest association with general obesity in women (OR, 3.01; 95%CI, 2.24-4.04) and with abdominal obesity based on the WHtR criterion in men (OR, 3.65; 95%CI, 2.66-5.01). Hypertriglyceridemia and low levels of high-density lipoprotein cholesterol showed the strongest association with abdominal obesity based on the WHtR criterion in women (OR, 2.49; 95%CI, 1.68-3.67 and OR, 2.70; 95%CI, 1.89-3.86) and with general obesity in men (OR, 2.06; 95%CI, 1.56-2.73 and OR, 1.68; 95%CI, 1.21-2.33). Prediabetes showed the strongest association with abdominal obesity based on the WHtR criterion in women (OR, 2.48; 95%CI, 1.85-3.33) and with abdominal obesity based on the WC criterion in men (OR, 2.33; 95%CI, 1.75-3.08). Conclusions: Abdominal obesity indicators showed the strongest association with the presence of prediabetes. The association of anthropometric indicators with hypertension and dyslipidemia showed heterogeneous results (AU)
Subject(s)
Humans , Male , Female , Adult , Middle Aged , Aged , Hypertension/epidemiology , Hypertension/prevention & control , Obesity/complications , Hyperlipidemias/complications , Prediabetic State/diagnosis , Obesity, Abdominal/complications , Hyperlipidemias/prevention & control , Prediabetic State/prevention & control , Anthropometry/methods , Waist-Height Ratio , Logistic Models , Blood Glucose/metabolismABSTRACT
This communication details a method for the quantitative and qualitative analysis of blood T-, B- and NK-cell populations using the Abbott Cell-Dyn CD4000 haematology analyser. A series of 66 ethylenediaminetetraacetic acid (EDTA)-anticoagulated samples with lymphocyte counts between 0.2 and 33.3 x 10(9)/l were selected and analysed with CD3, CD19, Ia and CD56 monoclonal reagents. The flow cytometry reference method utilized a lymphocyte gate defined by optical scatter, with phenotypic analyses referencing to this gate and the absolute lymphocyte count. The CD4000 method analysed all leucocyte events, set primary gates for specific immunophenotypic fractions, and then determined population counts by reference to the white blood cell (WBC) count. Comparisons of CD3+ T-cell and CD19+ B-cell numbers showed high coefficients of correlation (R(2) > 0.95) and agreement (y = 1.01x) between the CD4000 and flow cytometry reference methods. Lower coefficients of correlation were obtained for CD3-CD56+ (R(2) = 0.52) and CD3+CD56+ (R(2) = 0.83) components. No major discrepancies were observed, and the CD4000 procedures additionally provided qualitative insights into the possibility of T-cell activation. The potential to undertake immediate analysis of EDTA-anticoagulated blood samples to determine the nature of abnormal lymphocyte morphology or numbers represents a considerable advance in the capability of haematology laboratories.
